Analysis of Technology Potential of a Metal-based Latent Heat Storage for Backup Process Steam Supply

An analysis of technology potential of a metal-based high temperature latent heat storage for the application of process steam backup for industrial parks in Germany was carried out. To investigate the integration of the storage into a process steam network, dynamic process simulations were performed. Furthermore, the analysis includes ecological and economical calculations for various fuel types of industrial power plants, plant sizes and auxiliary fuels. Basis of all calculations is an extensive research conducted on the industrial parks in Germany with a dedicated power plant and process steam utilization.     

Absolute interferometric distance measurement using a FM-demodulation technique

We propose an interferometric method for measuring absolute distances larger than the wavelength. A laser diode is used as a light source. The principle of operation is based on multiple-wavelength interferometry that uses a modulated light source. This method uses the fact that the wavelength of light emitted by the laser diode can be varied by means of the injection current. The modulation of the injection current in combination with the optical heterodyne technique causes a high-frequency phase-modulated detector signal. The phase deviation of the signal is a measure of the optical path difference in the interferometer. By FM demodulation of the detector output with a phase-locked loop demodulator, the optical path difference can be determined directly without the classical ambiguity problem of interferometry. The measuring range in the experiments was limited to 50 mm by the maximum travel range of the used specimen translation stage. Because of the inherent light sensitivity of the method described, the rangefinder can be used for three-dimensional profile measurements on a wide variety of objects, even on diffuse scattering surfaces.     

Uniting Strength and Toughness of Al Matrix Composites with Coordinated Al3Ni and Al3Ti Reinforcements

Hybrid aluminum composites are fabricated in a novel manner to characteristically induce a layer‐wise aligned distribution of micro‐scale Al₃Ni and Al₃Ti intermetallic particles that are formed in situ within a ductile Al matrix. The simple and unique Rolling of Randomly Orientated Layer‐wise Materials (RROLM) manufacturing methodology enables microstructural tailoring of the intermetallic reinforcing particles to prescribe enhanced crack tip deflection caused by the complex interaction of local veins of reinforcement particles, in an effort to overshadow the classical loss of toughness in large‐particle reinforced composites. The complimentary reinforcements and their interface with the Al matrix are revealed to have a gradual transition zone that functions to maintain critical cohesion with the particles and the matrix, empowering the superior load transfer capability of the particles, and reducing microvoid penetration into the matrix. In situ three‐point bending observations combined with a local strain field analysis, demonstrate the distinctive crack deflection mechanisms exhibit by the composite. Deviating from the norm, this specialized particle reinforced composite exhibited both strengthening and toughening mechanisms simultaneously, over control samples. The investigated design strategy and model material will assist materials development toward light‐weight, stronger, and tougher particle reinforced Al matrix composites.     

Makespan minimization of multi-slot just-in-time scheduling on single and parallel machines

The paper addresses the problem of multi-slot just-in-time scheduling. Unlike the existing literature on this subject, it studies a more general criterion—the minimization of the schedule makespan rather than the minimization of the number of slots used by schedule. It gives an O(nlog ² n)-time optimization algorithm for the single machine problem. For arbitrary number of m>1 identical parallel machines it presents an O(nlog n)-time optimization algorithm for the case when the processing time of each job does not exceed its due date. For the general case on m>1 machines, it proposes a polynomial time constant factor approximation algorithm.     

Maximum throughput of multiple access channels in adversarial environments

We consider deterministic distributed broadcasting on multiple access channels in the framework of adversarial queuing. Packets are injected dynamically by an adversary that is constrained by the injection rate and the number of packets that may be injected simultaneously; the latter we call burstiness. A protocol is stable when the number of packets in queues at the stations stays bounded. The maximum injection rate that a protocol can handle in a stable manner is called the throughput of the protocol. We consider adversaries of injection rate 1, that is, of one packet per round, to address the question if the maximum throughput 1 can be achieved, and if so then with what quality of service. We develop a protocol that achieves throughput 1 for any number of stations against leaky-bucket adversaries. The protocol has O(n²+\textburstiness){\mathcal{O}(n^2+\text{burstiness})} packets queued simultaneously at any time, where n is the number of stations; this upper bound is proved to be best possible. A protocol is called fair when each packet is eventually broadcast. We show that no protocol can be both stable and fair for a system of at least two stations against leaky-bucket adversaries. We study in detail small systems of exactly two and three stations against window adversaries to exhibit differences in quality of broadcast among classes of protocols. A protocol is said to have fair latency if the waiting time of packets is O(\textburstiness){\mathcal{O}(\text{burstiness})}. For two stations, we show that fair latency can be achieved by a full sensing protocol, while there is no stable acknowledgment based protocol. For three stations, we show that fair latency can be achieved by a general protocol, while no full sensing protocol can be stable. Finally, we show that protocols that either are fair or do not have the queue sizes affect the order of transmissions cannot be stable in systems of at least four stations against window adversaries.     

Randomized mutual exclusion on a multiple access channel

In this paper we consider the mutual exclusion problem on a multiple access channel. Mutual exclusion is one of the fundamental problems in distributed computing. In the classic version of this problem, n processes execute a concurrent program that occasionally triggers some of them to use shared resources, such as memory, communication channel, device, etc. The goal is to design a distributed algorithm to control entries and exits to/from the shared resource (also called a critical section), in such a way that at any time, there is at most one process accessing it. In our considerations, the shared resource is the shared communication channel itself (multiple access channel), and the main challenge arises because the channel is also the only mean of communication between these processes. We consider both the classic and a slightly weaker version of mutual exclusion, called \(\varepsilon \)-mutual-exclusion, where for each period of a process staying in the critical section the probability that there is some other process in the critical section is at most \(\varepsilon \). We show that there are channel settings, where the classic mutual exclusion is not feasible even for randomized algorithms, while the \(\varepsilon \)-mutual-exclusion is. In more relaxed channel settings, we prove an exponential gap between the makespan complexity of the classic mutual exclusion problem and its weaker \(\varepsilon \)-exclusion version. We also show how to guarantee fairness of mutual exclusion algorithms, i.e., that each process that wants to enter the critical section will eventually succeed.     

Optimal Deterministic Broadcasting in Known Topology Radio Networks

We consider deterministic broadcasting in radio networks whose nodes have full topological information about the network. The aim is to design a polynomial algorithm, which, given a graph G with source s, produces a fast broadcast scheme in the radio network represented by G. The problem of finding a fastest broadcast scheme for a given graph is NP-hard, hence it is only possible to get an approximation algorithm. We give a deterministic polynomial algorithm which produces a broadcast scheme of length , for every n-node graph of diameter D, thus improving a result of Gąsieniec et al. (PODC 2005) [17] and solving a problem stated there. Unless the inclusion NP BPTIME( holds, the length of a polynomially constructible deterministic broadcast scheme is optimal.A preliminary version of this paper (with a weaker result) appeared in the Proc. 7th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX’2004), August 2004, Harvard University, Cambridge, USA, LNCS 3122, 171–182. Research of the second author supported in part by NSERC discovery grant and by the Research Chair in Distributed Computing of the Université du Québec en Outaouais. Part of this work was done during the second author’s visit at the Max-Planck-Institut für Informatik.     

Robust gossiping with an application to consensus

We study deterministic gossiping in synchronous systems with dynamic crash failures. Each processor is initialized with an input value called rumor. In the standard gossip problem, the goal of every processor is to learn all the rumors. When processors may crash, then this goal needs to be revised, since it is possible, at a point in an execution, that certain rumors are known only to processors that have already crashed. We define gossiping to be completed, for a system with crashes, when every processor knows either the rumor of processor v or that v has already crashed, for any processor v. We design gossiping algorithms that are efficient with respect to both time and communication. Let t<n be the number of failures, where n is the number of processors. If , then one of our algorithms completes gossiping in O(log²t) time and with O(npolylogn) messages. We develop an algorithm that performs gossiping with O(n^1.77) messages and in O(log²n) time, in any execution in which at least one processor remains non-faulty. We show a trade-off between time and communication in gossiping algorithms: if the number of messages is at most O(npolylogn), then the time has to be at least . By way of application, we show that if n−t=Ω(n), then consensus can be solved in O(t) time and with O(nlog²t) messages.     

An efficient algorithm for finding ideal schedules

We study the problem of scheduling unit execution time jobs with release dates and precedence constraints on two identical processors. We say that a schedule is ideal if it minimizes both maximum and total completion time simultaneously. We give an instance of the problem where the min-max completion time is exceeded in every preemptive schedule that minimizes total completion time for that instance, even if the precedence constraints form an intree. This proves that ideal schedules do not exist in general when preemptions are allowed. On the other hand, we prove that, when preemptions are not allowed, then ideal schedules do exist for general precedence constraints, and we provide an algorithm for finding ideal schedules in O(n ³) time, where n is the number of jobs. In finding such ideal schedules we resolve a conjecture of Baptiste and Timkovsky (Math. Methods Oper. Res. 60(1):145–153, 2004) Further, our algorithm for finding min-max completion-time schedules requires only O(n ³) time, while the most efficient solution to date has required O(n ⁹) time.     

Agent-based guided local search

The main contribution of the paper is to propose and validate a new hybrid approach for solving combinatorial optimization problems in which guided local search metaheuristic is incorporated into a cooperative multi-agent framework based on the concept of asynchronous teams (A-Teams). Generally, an A-Team assumes that a collection of software agents, each representing a particular problem solving method, cooperate to solve a problem by dynamically evolving a population of solutions. In the suggested implementation each software agent carries out a guided local search. The proposed approach has been extensively validated experimentally on one of the best known combinatorial optimization problem – the vehicle routing problem. The promising results of experiments have confirmed the effectiveness of the suggested approach.