Neuro-Fuzzy Modeling of the Free Convection Heat Transfer From a Wavy Surface

In this paper an adaptive neuro-fuzzy inference system (ANFIS) is applied to model and predict the experimental results of free convection heat transfer from a vertical array of attached cylinders, which can be considered as a wavy surface, in the presence of a vertical wall. The effects of the wall–wavy surface spacing and Rayleigh number variation on average heat transfer from the wavy surface are considered via this prediction. The training data for optimizing the ANFIS structure are based on available experimental data. A hybrid learning algorithm consisting of gradient descends method and least-squares method is used for ANFIS training. The proposed ANFIS model is developed using MATLAB functions. For the best ANFIS structure obtained in this study, the mean relative errors of the train and test data were found to be 0.02% and 1.2%, respectively. The predicted results showed that ANFIS can predict the experimental results precisely.     

Polymer nanocomposites processed via self-assembly through introduction of nanoparticles,nanosheets, and nanofibers

Nanocomposites offer the theoretical potential to achieve mechanical properties surpassing those of conventional (micro-scale) composites. The underlying reasons for the high potential of nanocomposites include the uniquely high mechanical attributes of nano-scale reinforcement, effective control of defect size and growth by nano-spaced interfaces, and interactions between the polymer matrix and the large surface areas of nanomaterials. Attempts to produce nanocomposites via conventional processing techniques have encountered challenges associated with thorough dispersion and effective interfacial interactions of nano-scale reinforcement with the polymer matrix. In order to address these challenges, materials were processed into polymer nanocomposites via electrostatically driven layer-by-layer self-assembly. Electrostatically dispersed nanomaterials and oppositely charged polyelectrolytes were sequentially built upon a substrate (cellular scaffold). The self-assembled nanocomposites, after complementary cross-linking, provided a unique balance of strength and ductility, which surpassed those of conventional (micro-scale) composites. Self-assembly was found to be an effective approach to producing nanocomposites embodying uniformly dispersed nanomaterials with controlled interfacial interactions. This approach is highly versatile and enables introduction of diverse nanomaterials into polymer nanocomposites. The work reported herein evaluated introduction of diverse categories of nanomaterials incorporating nanoparticles, nanosheets, nanotubes, and nanofibers. This investigation also evaluated the potential for a biomimetic approach to processing of light-weight structural systems by self-assembly of polymer nanocomposites onto cellular scaffolds.     

Quality of service constrained throughput optimisation for joint adaptive transmission with automatic repeat request over block-fading channels

An optimisation framework for wireless link adaptation which maximises the system throughput subject to a packet-level quality of service (QoS) constraint is presented. The authors consider joint adaptive variation of the transmitted power level, transmission data rate and packet-error-rate (PER) at the physical layer to improve the throughput performance of the selective-repeat automatic repeat request (SR-ARQ) protocol over block-fading channels. Specifically, for discrete-rate coded M-QAM schemes, the authors present a power and rate adaptation algorithm that guarantees a target PER constraint. The proposed framework also facilitates optimising the throughput performance for delay constrained wireless applications, which imposes a limit on the number of retransmissions for the ARQ. In particular, a link adaptation scheme is presented, which guarantees a target packet-loss rate (PLR) when a truncated SR ARQ protocol at the data-link layer is employed. Numerical results indicate that the proposed adaptation schemes compared with other adaptive schemes noticeably enhance the system throughput. Also, in the case of truncated ARQ, the results illustrate a fundamental trade-off between the delay and PLR QoS metrics achieved at the maximum throughput performance.