A multi-dimensional approach to the assessment of tunnel excavation methods

Selection of tunnel excavation method in rock calls for an exact assessment of engineering geology as well as geotechnical conditions of the tunnel strike. Moreover, uncertainties related to properties of engineering geology of rock often trigger complexity. In order to select the best possible excavation technique, one needs to take into account numerous operational, economic, environmental factors, and so forth. Using a hybrid methodology, including multiple attributes decision-making techniques and fuzzy set theory, the present study aims to evaluate the excavation methods of tunnels. The proposed approach is based on fuzzy-AHP and TOPSIS methods where the fuzzy-AHP determines weights of the criteria by decision makers in uncertain environment and TOPSIS concludes rankings of the excavation methods. Finally, a case study of Ghomroud project in Iran is presented to demonstrate the result of the proposed methodology.     

Shear wall layout optimization of tall buildings using Quantum Charged System Search

This paper presents a developed meta-heuristic algorithm to optimize the shear walls of tall reinforced concrete buildings. These types of walls are considered as lateral resistant elements. In this paper, Quantum Charged System Search (QCSS) algorithm is presented as a new optimization method and used to improve the convergence capability of the original Charged System Search. The cost of tall building is taken as the objective function. Since the design of the lateral system plays a major role in the performance of the tall buildings, this paper proposes a unique computational technique that, unlike available works, focuses on structural efficiency or architectural design. This technique considers both structural and architectural requirements such as minimum structural costs, torsional effects, flexural and shear resistance, lateral deflection, openings and accessibility. The robustness of the new algorithm is demonstrated by comparing the outcomes of the QCSS with those of its standard algorithm.     

Effect of nanoclay type on dyeability of polyethylene terephthalate/clay nanocomposites

Polyethylene terephthalate (PET)-based nanocomposites containing three differently modified clays were prepared by melt compounding. The influence of type of clay on disperseability, thermal, and dyeing properties of the resultant nanocomposite was investigated by various analytic techniques, namely, X-ray diffraction, optical microscopy (OPM), differential scanning calorimetry, thermal gravimetric analysis, dynamical mechanical thermal analysis, contact angle measurement (CAM), reflectance spectroscopy, and light fastness. OPM images illustrated formation of large-sized spherulites in pure PET, while only small-sized crystals appeared in PET/clay nanocomposites. Decreased glass transition temperatures for all PET/clay nanocomposites indicate that the amorphous regions of such composites become mobile at lower temperatures than those in pure PET. CAMs on the resultant PET composites demonstrated that the wettability of such composites depends on hydrophilicity of the nanoclay particles. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

The development of laminated composite plate theories: a review

This study investigates and reviews approaches to modelling laminated composite plates. It explores theories that have been proposed and developed and assesses their suitability and functionality. The particular focus in this study has been on normal stresses and the through-thickness distributions of transverse shear. These are important for composite plates as stress-induced failures can occur in three different ways. Therefore, it is essential to understand and calculate transverse shear and normal stress through the thickness of the plate accurately. In this study, previous laminated composite plate theories are categorised and reviewed in a general sense, i.e. not problem specific, and the advantages and disadvantages of each model are discussed. This research mainly focuses on how accurate and efficient the models can predict the transverse shear. It starts with displacement-based theories from very basic models such as Classical laminate plate theory to more complicated and higher-order shear deformation theory. Models are furthermore categorised by how the models consider the overall laminate. In this article, the theories are divided into two parts: Single layer theory, where the whole plate is considered as one layer; and Layerwise theory, where each layer is treated separately. The models based on zig-zag and Discrete Theories are then reviewed, and finally the mixed (hybrid) plate theories are studied.     

Two-stage energy-optimal formation reconfiguration strategy

In this paper, the concept of two-stage energy-optimal reconfiguration strategy for formation flying of autonomous agents is presented. It is desired to move the agents to a special designated formation in the idle time (the time between the completion of the current formation mission and the issuance of the next reconfiguration command), in order to minimize the expected value of the reconfiguration energy consumption. The position of each agent in the special designated formation is obtained as a function of the agent’s current position and the weighted center of gravity of the set of possible positions for that agent. It is shown that this strategy can reduce energy consumption considerably compared to conventional strategies. In the case of constrained acceleration, it is shown that the results remain the same as the unconstrained case if the reconfiguration time is sufficiently longer than its minimum possible value. The effectiveness of the proposed strategy is illustrated by simulation.     

A Spatial‐Bayesian Technique for Imputing Pavement Network Repair Data

Abstract: Pavement construction and repair history is necessary for several pavement management functions such as developing pavement condition prediction models and developing maintenance and rehabilitation (M&R) trigger values based on past repair frequencies. It is often difficult to integrate M&R data with condition data since these data are often stored in disparate heterogeneous databases. This article provides a computational technique for estimating construction and M&R history of a pavement network from the spatiotemporal patterns of its condition data. The technique is founded on Bayesian and spatial statistics and searches pavement condition data in groups of adjacent pavement sections for evidence of repair. The developed technique was applied to a pavement network in Texas and has been found to have a 74% precision and a 95% accuracy in estimating repair history data.     

Shelf life and delivery enhancement of vitamin C using chitosan nanoparticles

Chitosan with different molecular masses was reacted with sodium tripolyphosphate (STPP) to prepare different size nanoparticles, in which vitamin C was encapsulated. The effect of molecular weight (Mw) on nanoparticles efficiency, nanoparticles yield, size, and zeta potential was investigated in detail. Low Mw chitosan generated nanoparticles with better size, morphology, and delivery rate. In addition, the shelf life of encapsulated vitamin C increased as compared with its non-encapsulated counterpart. The release of vitamin C from the nanoparticles was pH-dependent. Quick release took place in 0.1 M phosphate buffer solution (PBS, pH 7.4), while the release was slow in 0.1 M HCl. In addition, in vivo release rate in digestive tract of rainbow trout nearly showed the same trend as the in vitro one.