CFRP-Steel hybrid retrofitting of steel-concrete composite structures

Carbon fiber reinforced polymer (CFRP) is found to be an effective material for the retrofitting of both reinforced concrete (RC) and steel structures. However, retrofitting such structures using CFRP alone is shown to exhibit a premature failure due to early de-bonding of the CFRP laminates from the hosting sur-faces. On the other hand, steel plates are also used separately for the steel and RC structures. However, steel plates usually add the self-weight to the structures whereas CFRP is known for its high strength to weight ra-tio. In the present study, the advantages of both steel plates and CFRP is used to form a hybrid retrofitting sys-tem that is able to withstand the existing load to prevent the failure of the structures. In order to improve the retrofitting efficiency of a steel-concrete composite structures, an experimental investigation is carried out to examine the use of effectiveness of CFRP-steel hybrid retrofitting system.

The osteogenic properties of CaP/silk composite scaffolds

The rationale for the present study was to develop porous CaP/silk composite scaffolds with a CaP-phase distribution and pore architecture better suited to facilitate osteogenic properties of human bone mesenchymal stromal cells (BMSCs) and in vivo bone formation abilities. This was achieved by first preparing CaP/silk hybrid powders which were then incorporated into silk to obtain uniform CaP/silk composite scaffolds, by means of a freeze-drying method. The composition, microstructure and mechanical properties of the CaP/silk composite scaffolds were ascertained by X-ray diffraction (XRD), Fourier transform infrared spectra (FTIR), scanning electron microscope (SEM) and a universal mechanical testing machine. BMSCs were cultured in these scaffolds and cell proliferation analyzed by confocal microscopy and MTS assay. Alkaline phosphatase (ALP) activity and osteogenic gene expression were assayed to determine if osteogenic differentiation had taken place. A calvarial defect model in SCID mice was used to determine the in vivo bone forming ability of the hybrid CaP/silk scaffolds. Our results showed that incorporating the hybrid CaP/silk powders into silk scaffolds improved both pore structure architecture and distribution of CaP powders in the composite scaffolds. By incorporating the CaP phase into silk scaffolds in vitro osteogenic differentiation of BMSCs was enhanced and there was increased in vivo cancellous bone formation. Here we report a method with which to prepare Ca/P composite scaffolds with a pore structure and Ca/P distribution better suited to facilitate BMSC differentiation and bone formation.

A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition

Web service composition is an important problem in web service based systems. It is about how to build a new value-added web service using existing web services. A web service may have many implementations, all of which have the same functionality, but may have different QoS values. Thus, a significant research problem in web service composition is how to select a web service implementation for each of the web services such that the composite web service gives the best overall performance. This is so-called optimal web service selection problem. There may be mutual constraints between some web service implementations. Sometimes when an implementation is selected for one web service, a particular implementation for another web service must be selected. This is so called dependency constraint. Sometimes when an implementation for one web service is selected, a set of implementations for another web service must be excluded in the web service composition. This is so called conflict constraint. Thus, the optimal web service selection is a typical constrained ombinatorial optimization problem from the computational point of view. This paper proposes a new hybrid genetic algorithm for the optimal web service selection problem. The hybrid genetic algorithm has been implemented and evaluated. The evaluation results have shown that the hybrid genetic algorithm outperforms other two existing genetic algorithms when the number of web services and the number of constraints are large.

Interfacial debonding behavior of composite beam/plates with PZT patch

This paper studies interfacial debonding behavior of composite beams which include piezoelectric materials, adhesive and host beam. The focus is put on crack initiation and growth of the piezoelectric adhesive interface. Closed-form solutions of interface stresses and energy release rates are obtained for adhesive layer in the piezoelectric composite beams. Finite element analyses have been carried out to study the initiation and growth of interfaces crack for piezoelectric beams with interface element by ANSYS, in which the interface element of FE model is based on the cohesive zone models to characterize the fracture behavior of the interfacial debonding. The results have been compared with analystical solution, and the influence of different geometry and material parameters on the interfacial behavior of piezoelectric composite beams have been discussed.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

A review of optimization techniques used in the design of fibre composite structures for civil engineering applications

Fibre composite structures have become the most attractive candidate for civil engineering applications. Fibre reinforced plastic polymer (FRP) composite materials have been used in the rehabilitation and replacement of the old degrading traditional structures or build new structures. However, the lack of design standards for civil infrastructure limits their structural applications. The majority of the existing applications have been designed based on the research and guidelines provided by the fibre composite manufacturers or based on the designer’s experience. It has been a tendency that the final structure is generally over-designed. This paper provides a review on the available studies related to the design optimization of fibre composite structures used in civil engineering such as; plate, beam, box beam, sandwich panel, bridge girder, and bridge deck. Various optimization methods are presented and compared. In addition, the importance of using the appropriate optimization technique is discussed. An improved methodology, which considering experimental testing, numerical modelling, and design constrains, is proposed in the paper for design optimization of composite structures.

Hybrid graphene and graphitic carbon nitride nanocomposite : gap opening, electron–hole puddle, interfacial charge transfer, and enhanced visible light response

Opening up a band gap and finding a suitable substrate material are two big challenges for building graphene-based nanodevices. Using state-of-the-art hybrid density functional theory incorporating long range dispersion corrections, we investigate the interface between optically active graphitic carbon nitride (g-C3N4) and electronically active graphene. We find an inhomogeneous planar substrate (g-C3N4) promotes electronrich and hole-rich regions, i.e., forming a well-defined electron−hole puddle, on the supported graphene layer. The composite displays significant charge transfer from graphene to the g-C3N4 substrate, which alters the electronic properties of both components. In particular, the strong electronic coupling at the graphene/g-C3N4 interface opens a 70 meV gap in g-C3N4-supported graphene, a feature that can potentially allow overcoming the graphene’s band gap hurdle in constructing field effect transistors. Additionally, the 2-D planar structure of g-C3N4 is free of dangling bonds, providing an ideal substrate for graphene to sit on. Furthermore, when compared to a pure g-C3N4 monolayer, the hybrid graphene/g-C3N4 complex displays an enhanced optical absorption in the visible region, a promising feature for novel photovoltaic and photocatalytic applications.

Preparation of porous nanofibers from electrospun polyacrylonitrile/calcium carbonate composite nanofibers using porogen leaching technique

Production of nanofibrous polyacrylonitrile/calcium carbonate (PAN/CaCO3) nanocomposite web was carried out through solution electrospinning process. Pore generating nanoparticles were leached from the PAN matrices in hydrochloric acid bath with the purpose of producing an ultimate nanoporous structure. The possible interaction between CaCO3 nanoparticles and PAN functional groups was investigated. Atomic absorption method was used to measure the amount of extracted CaCO3 nanoparticles. Morphological observation showed nanofibers of 270–720 nm in diameter containing nanopores of 50–130 nm. Monitoring the governing parameters statistically, it was found that the amount of extraction (ε) of CaCO3was increased when the web surface area (a) was broadened according to a simple scaling law (ε = 3.18 a0.4). The leaching process was maximized in the presence of 5% v/v of acid in the extraction bath and 5 wt % of CaCO3 in the polymer solution. Collateral effects of the extraction time and temperature showed exponential growth within a favorable extremum at 50°C for 72 h. Concentration of dimethylformamide as the solvent had no significant impact on the extraction level.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Locating delamination in composite laminated beams using the A0 Lamb mode

In this study, experimental and numerical investigations have been conducted to explore the possibility of using A0 mode in Lamb waves to detect the position of delamination in carbon fiber reinforced plastic (CFRP) laminated beams. An experimental technique for exciting and sensing the pure A0 mode has been developed. By measuring the propagation speed of A0 mode and traveling time of a signal reflected from the delamination, its location can be identified experimentally and numerically. Moreover, the numerical analysis has been extended to gain a better understanding of the complex interaction between A0 mode and a long delamination case.

In-situ combustion synthesis of ultrafine TiB2 particles reinforced Cu matrix composite

Due to the lower strength of pure copper (Cu), ceramic particulate or whisker reinforced Cu matrix composites have attracted wide interest in recent years [1–3]. These materials exhibit a combination of excellent thermal and electrical conductivities, high strength retention at elevated temperatures, and high microstructural stability [3]. The potential applications include various electrodes, electrical switches, and X-ray tube components [4].

Tensile properties of a boron/nitrogen-doped carbon nanotube–graphene hybrid structure

Doping is an effective approach that allows for the intrinsic modification of the electrical and chemical properties of nanomaterials. Recently, a graphene and carbon nanotube hybrid structure (GNHS) has been reported, which extends the excellent properties of carbon-based materials to three dimensions. In this paper, we carried out a first-time investigation on the tensile properties of the hybrid structures with different dopants. It is found that with the presence of dopants, the hybrid structures usually exhibit lower yield strength, Young’s modulus, and earlier yielding compared to that of a pristine hybrid structure. For dopant concentrations below 2.5% no significant reduction of Young’s modulus or yield strength could be observed. For all considered samples, the failure is found to initiate at the region where the nanotubes and graphene sheets are connected. After failure, monatomic chains are normally observed around the failure region. Dangling graphene layers without the separation of a residual CNT wall are found to adhere to each other after failure with a distance of about 3.4 Å. This study provides a fundamental understanding of the tensile properties of the doped graphene–nanotube hybrid structures, which will benefit the design and also the applications of graphene-based hybrid materials.