Performance optimization of polymer electrolyte membrane fuel cells using the Nelder-Mead algorithm

The direct-search simplex method for function optimization has been adapted to performance optimization of polymer electrolyte membrane fuel cells (PEMFCs). The established method is strongly application oriented and uses only experimentally determined data for optimization. It is not restricted to discrete parameters optimums and does not require the use of third-party software or computational resources. Hence, it is easy to implement in fuel cell testing stations. The optimization consists of finding, for a given fuel cell load, an optimum set of values of the 7 fuel cell operating parameters: the fuel cell temperature, the reactants' stoichiometric ratios, the reactants' inlet relative humidity, and the reactants' outlet pressures, resulting in the highest fuel cell performance. The performance is measured using a scalar function of the operating parameters and the load and can be defined according to needs.Two PEMFC performance functions: the fuel cell voltage and the system-related fuel cell efficiency were optimized using the procedure for practically sized PEMFC stacks of two designs. With respect to the nominal operating conditions defined as optimal for each stack design by its manufacturer, the gains from the optimization procedure were up to over 12% and up to over 7% for the stack voltage and efficiency, respectively. The validation of the procedure involved 5 stack specimens and four laboratories and consistent results were obtained.     

Multiple insights call for revision of modern thermodynamic models to account for structural fluctuations in water

Modern thermodynamic models incorporate the concept of association (hydrogen bonding) and they can describe very satisfactorily many properties of water containing mixtures. They have not been successful in representing water's anomalous properties and this work provides a possible explanation. We have analyzed and interpreted recent experimental data, molecular simulation results, and two-state theory approaches and compared against the predictions from thermodynamic models. We show that the dominance of the tetrahedral structure implemented in modern thermodynamic models may be the reason for their failure for describing water systems. While this study does not prove the two-state theories for water, it indicates that a high level of tetrahedral structure of water is not in agreement with water's anomalous properties when used in thermodynamic models.     

Non‐Toxic Dry‐Coated Nanosilver for Plasmonic Biosensors

The plasmonic properties of noble metals facilitate their use for in vivo bio‐applications such as targeted drug delivery and cancer cell therapy. Nanosilver is best suited for such applications as it has the lowest plasmonic losses among all such materials in the UV‐visible spectrum. Its toxicity, however, can destroy surrounding healthy tissues and thus, hinders its safe use. Here, that toxicity against a model biological system (Escherichia coli) is “cured” or blocked by coating nanosilver hermetically with a about 2 nm thin SiO₂ layer in one‐step by a scalable flame aerosol method followed by swirl injection of a silica precursor vapor (hexamethyldisiloxane) without reducing the plasmonic performance of the enclosed or encapsulated silver nanoparticles (20–40 nm in diameter as determined by X‐ray diffraction and microscopy). This creates the opportunity to safely use powerful nanosilver for intracellular bio‐applications. The label‐free biosensing and surface bio‐functionalization of these ready‐to‐use, non‐toxic (benign) Ag nanoparticles is presented by measuring the adsorption of bovine serum albumin (BSA) in a model sensing experiment. Furthermore, the silica coating around nanosilver prevents its agglomeration or flocculation (as determined by thermal annealing, optical absorption spectroscopy and microscopy) and thus, enhances its biosensitivity, including bioimaging as determined by dark field illumination.     

Performance evaluation of ad hoc routing protocols for military communications

Mobile ad hoc networks (MANETs) are of much interest to both the research community and the military because of the potential to establish a communication network in any situation that involves emergencies. Examples are search‐and‐rescue operations, military deployment in hostile environments, and several types of police operations. One critical open issue is how to route messages considering the characteristics of these networks. The nodes act as routers in an environment without a fixed infrastructure, the nodes are mobile, the wireless medium has its own limitations compared to wired networks, and existing routing protocols cannot be employed, at least without modifications. Over the last few years, a number of routing protocols have been proposed and enhanced to address the issue of routing in MANETs. It is not clear how those different protocols perform under different environments. One protocol may be the best in one network configuration but the worst in another. This article provides an analysis and performance evaluation of those protocols that may be suitable for military communications. The evaluation is conducted in two phases. In the first phase, we compare the protocols based on qualitative metrics to locate those that may fit our evaluation criteria. In the second phase, we evaluate the selected protocols from the first phase based on quantitative metrics in a mobility scenario that reflects tactical military movements. The results disclose that there is no routing protocol in the current stage without modifications that can provide efficient routing to any size of network, regardless of the number of nodes and the network load and mobility. Copyright © 2011 John Wiley & Sons, Ltd.     

Anchor‐free distance estimation: A new approach to distance estimation for multihop ad hoc wireless networks

In ad hoc wireless networks, devices that normally cannot directly communicate route their messages through intermediate nodes. The number of those nodes is called hop count, a useful metric in estimating the distance between 2 nodes. Current methods usually depend on special nodes, called anchors, that need accurate localization information, in order to calculate an estimate for the average distance traversed per hop. The drawback of this approach is that anchor nodes increase the overall cost and complexity of the system. To address this problem, this letter proposes a novel, anchor node–free algorithm that can achieve a useful estimate for actual distance between 2 nodes, by analytically finding an estimate for the average maximum distance traveled per hop and multiplying with the hop count. The only requirement is the a priori knowledge of the networks' node density and the node range. The performance of our method is compared with a recent anchor node–based method and is shown to yield similar location estimation accuracy, despite the fact that it does not use anchor nodes.     

Cross-layer modeling of adaptive wireless links for QoS support in heterogeneous wired-wireless networks

Future wired-wireless multimedia networks require diverse quality-of-service (QoS) support. To this end, it is essential to rely on QoS metrics pertinent to wireless links. In this paper, we develop a cross-layer model for adaptive wireless links, which enables derivation of the desired QoS metrics analytically from the typical wireless parameters across the hardware-radio layer, the physical layer and the data link layer. We illustrate the advantages of our model: generality, simplicity, scalability and backward compatibility. Finally, we outline its applications to power control, TCP, UDP and bandwidth scheduling in wireless networks. The work by Q. Liu and G. B. Giannakis are prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The work by S. Zhou is supported by UConn Research Foundation internal grant 445157. Qingwen Liu (S’04) received the B.S. degree in electrical engineering and information science in 2001, from the University of Science and Technology of China (USTC). He received the M.S. degree in electrical engineering in 2003, from the University of Minnesota (UMN). He currently pursues his Ph.D. degree in the Department of Electrical and Computer Engineering at the University of Minnesota (UMN). His research interests lie in the areas of communications, signal processing, and networking, with emphasis on cross-layer analysis and design, quality of service support for multimedia applications over wired-wireless networks, and resource allocation. Shengli Zhou (M’03) received the B.S. degree in 1995 and the M.Sc. degree in 1998, from the University of Science and Technology of China (USTC), both in electrical engineering and information science. He received his Ph.D. degree in electrical engineering from the University of Minnesota, 2002, and joined the Department of Electrical and Computer Engineering at the University of Connecticut, 2003. His research interests lie in the areas of communications and signal processing, including channel estimation and equalization, multi-user and multi-carrier communications, space time coding, adaptive modulation, and cross-layer designs. He serves as an associate editor for IEEE Transactions on Wireless Communications since Feb. 2005. G. B. Giannakis (Fellow’97) received his Diploma in Electrical Engineering from the National Technical University of Athens, Greece, 1981. From September 1982 to July 1986 he was with the University of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engineering, 1986. After lecturing for one year at USC, he joined the University of Virginia in 1987, where he became a professor of Electrical Engineering in 1997. Since 1999 he has been a professor with the Department of Electrical and Computer Engineering at the University of Minnesota, where he now holds an ADC Chair in Wireless Telecommunications. His general interests span the areas of communications and signal processing, estimation and detection theory, time-series analysis, and system identification -- subjects on which he has published more than 200 journal papers, 350 conference papers and two edited books. Current research focuses on transmitter and receiver diversity techniques for single- and multi-user fading communication channels, complex-field and space-time coding, multicarrier, ultra-wide band wireless communication systems, cross-layer designs and sensor networks. G. B. Giannakis is the (co-) recipient of six paper awards from the IEEE Signal Processing (SP) and Communications Societies (1992, 1998, 2000, 2001, 2003, 2004). He also received the SP Society’s Technical Achievement Award in 2000. He served as Editor in Chief for the IEEE SP Letters, as Associate Editor for the IEEE Trans. on Signal Proc. and the IEEE SP Letters, as secretary of the SP Conference Board, as member of the SP Publications Board, as member and vice-chair of the Statistical Signal and Array Processing Technical Committee, as chair of the SP for Communications Technical Committee and as a member of the IEEE Fellows Election Committee. He has also served as a member of the IEEE-SP Society’s Board of Governors, the Editorial Board for the Proceedings of the IEEE and the steering committee of the IEEE Trans. on Wireless Communications.     

Minimum Moment Method for Resource Leveling Using Entropy Maximization

The minimum moment method for resource leveling is revisited and restated as an entropy-maximization problem. The minimum moment method assumes that the moment of the daily resource demands about the horizontal axis of a project’s resource histogram is a good measure of the resource utilization and that the optimal resource allocation exists when the total moment is at a minimum, thus when the resource histogram is of rectangular shape. The entropy-maximization method proposed in this paper makes use of the general theory of entropy and two of its principal properties (subadditivity and maximality) to revisit the minimum moment method for resource leveling. The entropy-maximization method presented allows for activity stretching and provides resource allocation solutions that show improvement over previous approaches. A case study is also presented that validates the results.