Application of support vector machines in scour prediction on grade-control structures

Research into the problem of predicting the maximum depth of scour on grade-control structures like sluice gates, weirs and check dams, etc., has been mainly of an experimental nature and several investigators have proposed a number of empirical relations for a particular situation. These traditional scour prediction equations, although offer some guidance on the likely magnitude of maximum scour depth, yet applicable to a limited range of the situations. It appears from the literature review that a regression mathematical model for predicting maximum depth of scour under all circumstances is not currently available. This paper explores the potential of support vector machines in modeling the scour from the available laboratory and field data obtained form the earlier published studies. To compare the results, a recently proposed empirical relation and a feed forward back propagation neural network model are also used in the present study. The outcome from the support vector machines-based modeling approach suggests a better performance in comparison to both the empirical relation and back propagation neural network approach with the laboratory data. The results also suggest an encouraging performance by the support vector machines learning technique in comparison to both empirical relation as well as neural network approach in scaling up the results from laboratory to field conditions for the purpose of scour prediction.     

Behaviour of concrete-filled steel tubular columns incorporating fly ash

The subject of this work is to investigate the effect of fly ash on the strength of concrete filled steel tubular columns from 28 to 365 days. A contrast study was carried out on concrete filled steel tubular columns incorporating 10–40 wt% fly ash, and for control Portland cement concrete filled steel tubular columns. The effect of pre-coating the inner surface of steel tubes with a thin layer of fly ash was also studied. Assessments of the concrete mixes were based on the compressive strength and the bond strength. The results show that a lower replacement with fly ash can improve both bond strength and compressive strength, while a higher replacement with fly ash requires a relatively longer time to achieve similar beneficial effects. Pre-coating the inner surface of steel tubes with a thin layer of fly ash can notably improve the bond strength. The microstructure of the interface between concrete and steel tube was also studied by using scanning electron microscopy analyzer.     

Considerations in straight fold analysis of thin tubes under axial compression

A straight fold model for the analysis of the tubes under axial compression is reconsidered. Based on experiments, the tube is assumed to fold partly inside and partly outside the mean diameter of tube. The model considers the variation of circumferential strain during the formation of a fold, change in thickness of the tube during the deformation, and the influence of change in the yield strength of material in tension and compression. The first fold ends at the mean diameter and all subsequent folds initiate and end at the mean diameter. Some parameters have been introduced for making the expressions valid for first as well as the subsequent folds. The size of fold, load–compression curves, variation of inside and outside fold lengths and mean crushing load have been computed. All the variables involved in the analysis such as, the size of fold, folding parameter, mean crushing load, and the peak load have been obtained analytically. The model developed has been validated with the experiments.     

Application of soft-thresholding on the decomposed Lamb wave signals for damage detection of plate-like structures

Effective application of the Lamb waves for structural health monitoring and damage identification intensively relies on the accurate damage-related feature extraction in the received signals. Most of existing signal processing methods extract the damage-related features from the time–frequency joint spectrum which requires a quite amount of effort. In this paper, the soft-thresholding process, based on different signal decomposition methods, is introduced to damage identification so that the damage-related signal features can be manifested more distinctively. By applying two popular signal decomposition methods (i.e., the discrete wavelet transform (DWT) and the empirical mode decomposition (EMD)), the signal of interest can be represented by a series of components with different frequencies. Since most noises exist in the high frequency range, it is feasible to alleviate noise by restricting the energy of high-frequency components. Finally, a denoised signal is synthesized using the corresponding reconstruction method. As an application, the soft-thresholding process is performed to detect a small crack on an isotropic aluminum plate under the white Gaussian noise contamination. The results, from both the numerical finite element simulation and experimental test, indicate that the soft-thresholding process is capable of effectively reducing the effect of noise, convincingly improving the sensitivity of damage identification, and discriminating relatively small damage.     

Sublattice imbalance of substitutionally doped nitrogen in graphene

Motivated by the recently observed sublattice asymmetry of substitutional nitrogen impurities in CVD grown graphene, we show, in a mathematically transparent manner, that oscillations in the local density of states driven by the presence of substitutional impurities are responsible for breaking the sublattice symmetry. While these oscillations are normally averaged out in the case of randomly dispersed impurities, in graphene they have either the same, or very nearly the same, periodicity as the lattice. As a result, the total interaction energy of randomly distributed impurities embedded in the conduction-electron-filled medium does not vanish and is lowered when their configuration is sublattice-asymmetric. We also identify the presence of a critical concentration of nitrogen above which one should expect the sublattice asymmetry to disappear. This feature is not particular to nitrogen dopants, but should be present in other impurities.     

Electroactive shape memory polymer based on optimized multi-walled carbon nanotubes/polyvinyl alcohol nanocomposites

The development of shape memory polymers (SMPs) has gained remarkable attention due to their wide range of applications, from biomedical to electromechanical. In this work, we have developed and optimized an electroactive SMP based on polyvinyl alcohol/multi-walled carbon nanotubes (PVA/MWNTs) composites. When a constant voltage of 60 V was applied to the optimized sample, the polymer shape could be recovered to the original form within 35 s. Different weight fractions of MWNT/PVA composites were prepared by using a simple solution blending and transitional solution casting method, and their microstructures, electrical conductivities, thermal conductivities, and electroactive shape memory properties were investigated. According to our systematic analysis, the enhanced performance can be attributed to the reinforcement of MWNTs that led to the improved electrical and thermal conductivities of the PVA matrix.     

New training strategies for neural networks with application to quaternary Al–Mg–Sc–Cr alloy design problems

This study concerns the training of a neural network in multiple stages considering minimization of errors from multiple data/pattern resources. The paper proposed a dual stage multi-resource data training scheme using multi-objective genetic algorithm. The training scheme has been used for the design and development of efficient neural network model focusing on missing, but most informative domains of the data set by means of introducing only a few patterns from missing domain treated separately during the later stage of training. The trained model has been used to design a quaternary Al–Mg–Cr–Sc alloy system, from the information subsets of binary Al–Cr and the ternary Al–Mg–Sc alloys. The validity of the proposed algorithm has been discussed in light of the evolution of the ageing characteristics of the new aluminium alloy system.