Thermomechanical deformation behaviour of DH36 steel during friction stir welding by experimental validation and modelling

Friction stir welding is a solid state thermomechanical deformation process from which the plasticisation behaviour of the stirred material can be evaluated through the study of flow stress evolution. Flow stress data also supporting the development of a local microstructural numerical model have been generated. Hot compression testing of DH36 steel has been performed at a temperature range of 700–1100°C and strain rates from 10^?3 to 10² s^?1 to study the alloy’s thermomechanical deformation behaviour in conditions that simulate the actual friction stir welding process. It has been found that the evolution of flow stress is significantly affected by the test temperature and deformation rate. The material’s constitutive equation and constants have been calculated after analysis of these data. Preliminary numerical analysis results are in good agreement with experimental observations.     

On the transport capacity of Gaussian multiple access and broadcast channels

We study the transport capacity of the Gaussian multiple access channel (MAC), which consists of multiple transmitters and a single receiver, and the Gaussian broadcast channel (BC), which consists of a single transmitter and multiple receivers. The transport capacity is defined as the sum, over all transmitters (for the MAC) or receivers (for the BC), of the product of the data rate with a reward r(x) which is a function of the distance x that the data travels. In the case of the MAC, assuming that the sum of the transmit powers is upper bounded, we calculate in closed form the optimal power allocation among the transmitters, that maximizes the transport capacity, using Karush-Kuhn-Tucker (KKT) conditions. We also derive asymptotic expressions for the optimal power allocation, that hold as the number of transmitters approaches infinity, using the most-rapid-approach method of the calculus of variations. In the case of the BC, we calculate in closed form the optimal allocation of the transmit power among the signals to the different receivers, both for a finite number of receivers and for the case of asymptotically many receivers, using our results for the MAC together with duality arguments. Our results can be used to gain intuition and develop good design principles in a variety of settings. For example, they apply to the uplink and downlink channel of cellular networks, and also to sensor networks which consist of multiple sensors that communicate with a single central station. Work was carried out while all authors were with the Telecommunications Research Center Vienna (ftw.), and supported by K plus funding for the ftw. project I0 “Signal and Information Processing.” Parts of this work have appeared, in preliminary form, in [1,2,3], Gautam A. Gupta holds a joint B.S./M.S. degree in mathematics and computing at the Department of Mathematics of the Indian Institute of Technology at New Delhi. During the summer of 2003, he attended a summer course on Probability and Statistical Mechanics organized by the Scoula Normale Superiore, in Pisa, Italy. During the summers of 2004 and 2005 he worked at the Telecommunications Research Center Vienna (ftw.) as a summer intern. During the spring of 2006, he was a visitor at the Norwegian University of Science and Technology, working toward his M. S. Thesis. Stavros Toumpis received the Diploma in electrical and computer engineering from the National Technical University of Athens, Greece, in 1997, the M.S. degrees in electrical engineering and mathematics from Stanford University, CA, in 1999 and 2002, respectively, and the Ph.D. degree in electrical engineering, also from Stanford, in 2003. From 1998 to 1999, he worked as a Research Assistant for the Mars Global Surveyor Radio Science Team, providing operational support. From 2000 to 2003, he was a Member of the Wireless Systems Laboratory, at Stanford University. From 2003 to 2005, he was a Senior Researcher with the Telecommunications Research Center Vienna (ftw.), in Vienna, Austria. Since 2005, he is a Lecturer at the Department of Electrical and Computer Engineering of the University of Cyprus. His research is on wireless ad hoc networks, with emphasis on their capacity, the effects of mobility on their performance, medium access control, and information theoretic issues. Jossy Sayir received his Dipl. El.-Ing. degree from the ETH Zurich in 1991. From 1991 to 1993, he worked as a development engineer for Motorola Communications in Tel Aviv, Israel, contributing to the design of the first digital mobile radio system ever produced by Motorola. He returned to ETH from 1993 to 1999, getting his PhD in 1999 under the supervision of Prof. J.L. Massey. The title of his thesis is “On Coding by Probability Transformation.” Since 2000, he has been employed at the Telecommunications Research Center (ftw) in Vienna, Austria, as a senior researcher. His research interests include iterative decoding methods, joint source and channel coding, numerical capacity computation algorithms, Markov sources, and wireless ad hoc and sensor networks. Since July 2002, he manages part of the strategic research activities at Ftw and supervises a group of researchers. He has taught courses on Turbo and related codes at Vienna University of Technology and at the University of Aalborg, Denmark. He has served on the organization committees of several international conferences and workshops. Ralf R. Müller was born in Schwabach, Germany, 1970. He received the Dipl.-Ing. and Dr.Ing. degree with distinction from University of Erlangen-Nuremberg in 1996 and 1999, respectively. From 2000 to 2004, he was with Forschungszentrum Telekommunikation Wien (Vienna Telecommunications Research Center) in Vienna, Austria. Since 2005 he has been a full professor at the Department of Electronics and Telecommunications at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. He held visiting appointments at Princeton University, U.S.A., Institute Eurecom, France, The University of Melbourne, Australia, and The National University of Singapore and was an adjunct professor at Vienna University of Technology. Dr. Müller received the Leonard G. Abraham Prize (jointly with Sergio S. Verdú) from the IEEE Communications Society and the Johann-Philipp-Reis Prize (jointly with Robert Fischer). He was also presented an award by the Vodafone Foundation for Mobile Communications and two more awards from the German Information Technology Society (ITG). Dr. Müller is currently serving as an associate editor for the IEEE Transactions on Information Theory.     

Optimal deployment of large wireless sensor networks

A spatially distributed set of sources is creating data that must be delivered to a spatially distributed set of sinks. A network of wireless nodes is responsible for sensing the data at the sources, transporting them over a wireless channel, and delivering them to the sinks. The problem is to find the optimal placement of nodes, so that a minimum number of them is needed. The critical assumption is made that the network is massively dense, i.e., there are so many sources, sinks, and wireless nodes, that it does not make sense to discuss in terms of microscopic parameters, such as their individual placements, but rather in terms of macroscopic parameters, such as their spatial densities. Assuming a particular interference-limited, capacity-achieving physical layer, and specifying that nodes only need to transport the data (and not to sense them at the sources, or deliver them at the sinks once their location is reached), the optimal node placement induces a traffic flow that is identical to the electrostatic field created if the sources and sinks are replaced by a corresponding distribution of positive and negative charges. Assuming a general model for the physical layer, and specifying that nodes must not only transport the data, but also sense them at the sources and deliver them at the sinks, the optimal placement of nodes is given by a scalar nonlinear partial differential equation found by calculus of variations techniques. The proposed formulation and derived equations can help in the design of large wireless sensor networks that are deployed in the most efficient manner, not only avoiding the formation of bottlenecks, but also striking the optimal balance between reducing congestion and having the data packets follow short routes.     

On asymptotically optimal routing in large wireless networks and Geometrical Optics analogy

This work is based on the observation that, as the number of nodes in a wireless network approaches infinity, minimum cost routes become smooth curves that observe the same laws followed by rays of light in properly defined optical media. Accordingly, in this paper an analogy between optimal routing in large wireless networks and Geometrical Optics is first formally defined. The analogy is based on the concept of the cost function, which plays the role of the refractive index in the networking context. Then, the relevance of the principle of Fermat and the eikonal equation in routing problems is shown, and a methodology for calculating the cost function is proposed and applied in two cases of special interest, i.e., bandwidth limited and energy limited networks. The applicability of the Optics-Networking analogy is also discussed in the case of networks with large but finite numbers of nodes. Finally, novel, distributed route discovery protocols that make use of the analogy are outlined.     

Capacity regions for wireless ad hoc networks

We define and study capacity regions for wireless ad hoc networks with an arbitrary number of nodes and topology. These regions describe the set of achievable rate combinations between all source-destination pairs in the network under various transmission strategies, such as variable-rate transmission, single-hop or multihop routing, power control, and successive interference cancellation (SIC). Multihop cellular networks and networks with energy constraints are studied as special cases. With slight modifications, the developed formulation can handle node mobility and time-varying flat-fading channels. Numerical results indicate that multihop routing, the ability for concurrent transmissions, and SIC significantly increase the capacity of ad hoc and multihop cellular networks. On the other hand, gains from power control are significant only when variable-rate transmission is not used. Also, time-varying flat-fading and node mobility actually improve the capacity. Finally, multihop routing greatly improves the performance of energy-constraint networks.     

Numerical optimisation of laser assisted friction stir welding of structural steel

ABSTRACT

Significant progress has been made on the implementation of friction stir welding (FSW) in the industry for aluminium alloys. However, steel FSW and other high-temperature alloys is still the subject of considerable research, mainly because of the short life and high cost of the FSW tool. Different auxiliary energies have been considered as a means of optimising the FSW process and reducing the forces on the tool during the plunge and traverse stages, but numerical studies on steel are particularly limited. Building on the state-of-art, laser-assisted steel FSW has been numerically developed and analysed as a viable process amendment. Laser-assisted FSW increased the traverse speed up to 1500?mm?min^?1, significantly higher than conventional steel FSW. The application of laser assistance with a distance of 20?mm from the rotating tool reduced the reaction force on the tool probe tip up to 55% when compared to standard FSW.