Biaxial failure model for fiber reinforced concrete

Steel fiber reinforced concrete (SFRC) is widely applied in the construction industry. Numerical elastoplastic analysis of the macroscopic behavior is complex. This typically involves a piecewise linear failure curve including corner singularities. This paper presents a single smooth biaxial failure curve for SFRC based on a semianalytical approximation. Convexity of the proposed model is guaranteed so that numerical problems are avoided. The model has sufficient flexibility to closely match experimental results. The failure curve is also suitable for modeling plain concrete under biaxial loading. Since this model is capable of simulating the failure states in all stress regimes with a single envelope, the elastoplastic formulation is very concise and simple. The finite element implementation is developed to demonstrate the conciseness and the effectiveness of the model. The computed results display good agreement with published experimental data.

Evaluation of parameters effective in FRP shear strengthening of RC beams using FE method

Shear strengthening is required when an RC beam is found deficient in shear, or when its shear capacity falls below its flexural capacity after flexural strengthening. A recent technique for the shear strengthening of RC beams is to provide additional FRP web reinforcement, commonly in the form of bonded external FRP strips/sheets. Over the last few years, several experimental studies have been conducted on this new strengthening technique, which has established its effectiveness. While experimental methods of investigation are extremely useful in obtaining information about the composite behaviour of FRP and reinforced concrete, the use of numerical models such as the one presented in this paper helps in developing a good understanding of the behaviour at lower costs. In the study presented in this paper, ANSYS finite element program is used to examine the response of beams strengthened in shear by FRPs. The FE model is calibrated against test results performed at the University of Kentucky. Once validated, the model is used to examine the influence of fibre orientation, compressive strength of concrete, area of tensile and compressive reinforcements, and amount and distance between stirrups on the strength and ductility of FRP strengthened beam.

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

Knowledge-based system on optimum design of liquid retaining structures with genetic algorithms

This paper delineates the development of a prototype hybrid knowledge-based system for the optimum design of liquid retaining structures by coupling the blackboard architecture, an expert system shell VISUAL RULE STUDIO and genetic algorithm (GA). Through custom-built interactive graphical user interfaces under a user-friendly environment, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking, and member sizing optimization. For structural optimization, GA is applied to the minimum cost design of structural systems with discrete reinforced concrete sections. The design of a typical example of the liquid retaining structure is illustrated. The results demonstrate extraordinarily converging speed as near-optimal solutions are acquired after merely exploration of a small portion of the search space. This system can act as a consultant to assist novice designers in the design of liquid retaining structures.

A bayesian artificial neural network method to characterise laminar defects using dynamic measurements

This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.

Punching shear of slab-column connection in flat plate construction

The flat plate system is currently widely used in construction. It permits architectural flexibility, more clear space, less building height, easier formwork, and shorter construction time. However, there remains the problem of brittle punching failure due to the transfer of shearing forces and unbalanced moments at the flat plate-column connection. It is the purpose of this paper to investigate the effects of various interdependent factors that govern the punching shear resistance and behaviour of the flat plate-column connection, as well as their inclusion in current Codes.

Concrete finish, C House, Coorparoo, Brisbane

Concrete to house exterior.

Concrete finish, C House, Coorparoo, Brisbane

Concrete to house exterior.

Muscle fibre types and size distribution in sub-antarctic notothenioid fishes

The presumptive tonic muscles fibres of Cottoperca gobio, Champsocephalus esox, Harpagifer bispinis, Eleginops maclovinus, Patagonothen tessellata, P. cornucola and Paranotothenia magellanica stained weakly or were unstained for glycogen, lipid, succinic dehydrogenase (SDHase) and myosin ATPase (mATPase) activity. Slow, intermediate and fast twitch muscle fibres, distinguished on the basis of the pH stability of their mATPases, showed intense, moderate and low staining activity for SDHase, respectively. Slow fibres were the major component of the pectoral fin adductor profundis muscle. The proportion of different muscle fibre types varied from the proximal to distal end of the muscle, but showed relatively little variation between species. The myotomes contained a lateral superficial strip of red muscle composed of presumptive tonic, slow twitch and intermediate fibres, thickening to a major wedge at the horizontal septum. All species also had characteristic secondary dorsal and ventral wedges of red muscle. The relative abundance and localization of muscle fibre types in the red muscle varied between species and with body size in the protandric hermaphrodite E. maclovinus. The frequency distribution of diameters for fast twitch muscle fibres, the major component of deep white muscle, was determined in fish of a range of body sizes. The absence of fibres <20 mu m diameter was used as a criterion for the cessation of muscle fibre recruitment. Fibre recruitment had stopped in P, tessellata of 13.8 cm L-T and E, maclovinus of 32.8 cm L-T, equivalent to 49 and 36.5% of their recorded maximum sizes respectively. As a result in 20-cm P. tessellata, the maximum fibre diameter was 300 mu m and 36% of fibres were in excess of 200 mu m The unusually large maximum fibre diameter, the general arrangement of the red muscle layer and the extreme pH lability of the mATPase of fast twitch fibres are all common characters of the sub-Antarctic and Antarctic Notothenioids, including Cottoperca gobio, the suggested sister group to the Notothenidae. (C) 2000 The Fisheries Society of the British Isles.