• Earthquakes and Structures
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• v.11 no.6
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• pp.1101-1121
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• 2016

Base isolation, one of the popular seismic protection approaches proven to be effective in practical applications, has been widely applied worldwide during the past few decades. As the techniques mature, it has been recognised that, the biggest issue faced in base isolation technique is the challenge of great base displacement demand, which leads to the potential of overturning of the structure, instability and permanent damage of the isolators. Meanwhile, drain, ventilation and regular maintenance at the base isolation level are quite difficult and rather time- and fund- consuming, especially in the highly populated areas. To address these challenges, a number of efforts have been dedicated to propose new isolation systems, including segmental building, additional storey isolation (ASI) and mid-storey isolation system, etc. However, such techniques have their own flaws, among which whipping effect is the most obvious one. Moreover, due to their inherent passive nature, all these techniques, including traditional base isolation system, show incapability to cope with the unpredictable and diverse nature of earthquakes. The solution for the aforementioned challenge is to develop an innovative vibration isolation system to realise variable structural stiffness to maximise the adaptability and controllability of the system. Recently, advances on the development of an adaptive magneto-rheological elastomer (MRE) vibration isolator has enlightened the development of adaptive base isolation systems due to its ability to alter stiffness by changing applied electrical current. In this study, an innovative semi-active storey isolation system inserting such novel MRE isolators between each floor is proposed. The stiffness of each level in the proposed isolation system can thus be changed according to characteristics of the MRE isolators. Non-dominated sorting genetic algorithm type II (NSGA-II) with dynamic crowding distance (DCD) is utilised for the optimisation of the parameters at isolation level in the system. Extensive comparative simulation studies have been conducted using 5-storey benchmark model to evaluate the performance of the proposed isolation system under different earthquake excitations. Simulation results compare the seismic responses of bare building, building with passive controlled MRE base isolation system, building with passive-controlled MRE storey isolation system and building with optimised storey isolation system.

• Smart Structures and Systems
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• v.8 no.4
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• pp.343-365
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• 2011

Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

• Structural Engineering and Mechanics
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• v.16 no.5
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• pp.557-580
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• 2003

Laminated composite structures find wide range of applications in many branches of technology. They are much suited for weight sensitive structures (like aircraft) where thinner and lighter members made of advanced fiber reinforced composite materials are used. The orientations of fiber direction in layers and number of layers and the thickness of the layers as well as material of composites play a major role in determining the strength and stiffness. Thus the basic design problem is to determine the optimum stacking sequence in terms of laminate thickness, material and fiber orientation. In this paper, a new optimization technique called Cellular Automata (CA) has been combined with Genetic Algorithm (GA) to develop a different search and optimization algorithm, known as Cellular Genetic Algorithm (CGA), which considers the laminate thickness, angle of fiber orientation and the fiber material as discrete variables. This CGA has been successfully applied to obtain the optimal fiber orientation, thickness and material lay-up for multi-layered composite hybrid beams plates and shells subjected to static buckling and dynamic constraints.

• Structural Engineering and Mechanics
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• v.14 no.6
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• pp.625-647
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• 2002

Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

• Structural Engineering and Mechanics
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• v.47 no.5
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• pp.679-700
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• 2013

Two new predictive design methods are presented in this study. The first is a hybrid method, called neuro-fuzzy, based on neural networks with fuzzy learning. A total of 280 experimental datasets obtained from the literature concerning concentric punching shear tests of reinforced concrete slab-column connections without shear reinforcement were used to test the model (194 for experimentation and 86 for validation) and were endorsed by statistical validation criteria. The punching shear strength predicted by the neuro-fuzzy model was compared with those predicted by current models of punching shear, widely used in the design practice, such as ACI 318-08, SIA262 and CBA93. The neuro-fuzzy model showed high predictive accuracy of resistance to punching according to all of the relevant codes. A second, more user-friendly design method is presented based on a predictive linear regression model that supports all the geometric and material parameters involved in predicting punching shear. Despite its simplicity, this formulation showed accuracy equivalent to that of the neuro-fuzzy model.

• Computers and Concrete
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• v.26 no.4
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• pp.317-325
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• 2020

A precise estimation of the natural time period of buildings improves design quality, causes a significant reduction of the buildings' weight, and eventually leads to a cost-effective design. In this study, in order to optimise the reinforced concrete frames design, some symmetrical and unsymmetrical buildings composed of solid and hollow members have been simulated using finite element software SAP 2000. In numerical models, different parameters such as overturning moment, story drift, deflection, base reactions, and stiffness of the buildings were investigated and the results have been compared with strength and serviceability limit criteria proposed by Australian Standard (AS 3600 2018). Comparing the results of the numerical modelling with existing standards and performing a cost analysis proved the merits of hollow box sections compared to solid sections. Finally, based on numerical simulation results, two equations for natural time period of moment resisting reinforced concrete buildings have been presented. Both derived equations reflected higher degree of correlation and reliability with different complexities of building when compared with existing standards and relationships provided by other scholars. Therefore, these equations will assist practicing engineers to predict elastic behaivour of structures more precisely.

• Food Science of Animal Resources
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• v.29 no.5
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• pp.590-598
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• 2009

The aim of this study was to model and optimize the calcium alginate (CA) and microbial transglutaminase (TG) systems to form a cold-set myofibrillar protein (MP) gel containing 0.1 M or 0.3 M NaCl using a response surface methodology. The gel strengths of cold-set and heat-induced MP gels, and cooking yields were measured. All measured parameters showed determination coefficients ($R^2$) above 0.7 without a lack-of-fit. The CA system had the best results with component ratios of 1.0:0.3:1.0 corresponding to sodium alginate, calcium carbonate and glucono-$\delta$-lactone, respectively, and was favourable at 0.1 M NaCl. In contrast, the TG system only had an effect on cold-set MP gelation at 0.3 M salt, and the optimal ratio of TG to sodium caseinate was 0.6:0.5. By combining the two systems at 0.3 M NaCl, an acceptable cold-set MP gel with an improved texture and high cooking yield could be formed. Therefore, these results indicated that the functionality of the cold-set MP gel could be enhanced by combining these two optimized gelling system.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.427-442
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• 2012

An effective approach for updating finite element model is presented which can provide reliable estimates for structural updating parameters from identified operational modal data. On the basis of the dynamic perturbation method, an exact relationship between the perturbation of structural parameters such as stiffness change and the modal properties of the tested structure is developed. An iterative solution procedure is then provided to solve for the structural updating parameters that characterise the modifications of structural parameters at element level, giving optimised solutions in the least squares sense without requiring an optimisation method. A regularization algorithm based on the Tikhonov solution incorporating the generalised cross-validation method is employed to reduce the influence of measurement errors in vibration modal data and then to produce stable and reasonable solutions for the structural updating parameters. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is employed to demonstrate the effectiveness and applicability of the proposed model updating technique. The results from the benchmark problem studies show that the proposed technique can successfully adjust the reduced finite element model of the structure using only limited number of frequencies identified from the recorded ambient vibration measurements.

• Structural Engineering and Mechanics
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• v.52 no.6
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• pp.1085-1098
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• 2014

Plastic mechanism analysis of structures subjected to large deformation has long been used in order to determine collapse mechanisms of steel structures, and the energy absorbed in plastic deformation during such collapses. In this paper the technique is applied to vehicle roof structures that undergo large plastic deformation as a result of rollover crashes. The components of such roof structures are typically steel spot-welded hat-type sections. Ten different deformation mechanisms are defined from investigations of real-world rollover crashes, and an analytical technique to determine the plastic collapse load and energy absorption of such mechanisms is determined. The procedure is presented in a generic manner, such that it may be applied to any vehicle structure undergoing a rollover induced collapse. The procedure is applied to an exemplar vehicle, in order to demonstrate its application in determining the energy absorbed in the deformation of the identified collapse mechanisms. The procedure will be useful to forensic crash reconstructionists, in order to accurately determine the initial travel velocity of a vehicle that has undergone a rollover and for which the post-crash vehicle deformation is known. It may also be used to perform analytical studies of the collapse resistance of vehicle roof structures for optimisation purposes, which is also demonstrated with an analysis of the effect of varying the geometric and material properties of the roof structure components of the exemplar vehicle.

• Smart Structures and Systems
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• v.13 no.3
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• pp.389-406
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• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.