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This paper presents an extension of the basic truss layout optimization, in which the use of various materials is considered. A novel improved version of the particle swarm optimization algorithm, namely, GEMPSO, is developed for solving this problem. The enhancement is realized by introducing two core strategies: gradient estimation and multiple subpopulation division. The efficiency and reliability of the proposed improvements are demonstrated on a set of six test problems and three truss structures. Two multimaterial layout optimizations of truss structures are performed. The numerical results reveal that the appropriate partial use of expensive stronger materials can reduce the overall cost of multimaterial structures.

In this paper, a frame structural topology optimization methodology for the generation of moment resisting braced frames for tall buildings, considering dynamic seismic loading, is presented. Real-world loading conditions along with standardized steel profiles of Euronorm are employed. In the literature, the studies that employ the ground structure topology optimization method are limited mostly to truss structures under static loading conditions. The dynamic response in the framework of structural topology optimization remains a challenging problem, especially when the ground structure method is used for deriving the structural system of tall buildings. The contribution of this study to the state of the art, relies on the implementation of the proposed methodology in the conceptual design phase of civil engineering frame structures, where both axial and flexural stiffness is considered. Direct time integration methods are used, to implement forced vibrations and real recorded earthquake data in the topology optimization procedure, resulting to novel layouts for lateral resisting systems of tall buildings. Aiming to aid the engineer to the final design phase, the response spectrum modal analysis is employed and the seismic loading is applied according to the Eurocode 8.

We propose a new 8-node hexahedral element, the 3D-MITC8 element, for the analysis of three-dimensional solids. We use the MITC method and find the assumed strain field from a thought experiment using a truss idealization. For geometric nonlinear analysis, when needed to suppress hour-glass deformations, the formulation also uses automatically displacement-based contributions to the shear strains. The element shows a much better predictive capability than the displacement-based element. It is computationally more effective than the 8-node element with incompatible modes, and considering accuracy, in linear analysis performs almost as well, and in nonlinear analyses we do not observe spurious instabilities. We show that the new 3D solid element passes all basic tests (the isotropy, zero energy mode and patch tests) and present the finite element solutions of various benchmark problems to illustrate the solution accuracy reached with the new element.

This paper presents a novel adaptive hybrid evolutionary firefly algorithm (AHEFA) for shape and size optimization of truss structures under multiple frequency constraints. This algorithm is a hybridization of the differential evolution (DE) algorithm and the firefly algorithm (FA). An automatically adapted parameter is utilized to select an appropriate mutation scheme for an effective trade-off between the global and local search abilities. An elitist technique is applied to the selection phase to choose the best individuals. Accordingly, the convergence rate is significantly improved with the high solution accuracy. Six numerical examples are examined for the validity of the present algorithm.

A model for the non-linear dynamic behaviour of pre-stressed cable trusses is presented. The model provides the basis for a simplified description of the (in-plane) non-linear dynamical behaviour of biconcave and bi-convex cable structures (as well as of single cables) subject to different loading (and mass distribution) conditions. The simplicity of the proposed approach is coupled with its ability to schematically represent a wide range of actual structures, including light pedestrian suspended cable bridges and cable roofs with vertical harnesses, under different vertical loading conditions. Although aiming at the needs of the practitioner, in search for a simplified and intuitive understanding of the effects of nonlinearities on the dynamic response of cable structures (to confirm and explain results from more detailed FEM models), the proposed approach also paves the way for the investigation in the extensive taxonomy of the non-linear dynamic behaviour of cable structures. The present paper focuses on non-linear normal modes (NNMs) arising as a continuation of linear vibration modes of the structure when energy is increased. The identification of non-linear normal modes is achieved through harmonic balance; a time-integration analysis is then performed on the same model, with initial conditions derived from the harmonic balance approach, demonstrating consistent results. To further test the model, its behaviour is compared to simulations on a 66-degrees of freedom finite element truss model, with satisfactory results.

In this paper, an Enhanced Forensic-Based Investigation (EFBI) is proposed for optimal design of frequency-constrained dome-like trusses. The Forensic-Based Investigation (FBI) algorithm is a newly developed population-based metaheuristic inspired by the criminal investigation process. Throughout the FBI algorithm, the investigation and pursuit teams (i.e., the diversification and the intensification components of FBI, respectively) cooperate with each other to solve the target optimization problem. This study aims to modify the original formulation of FBI and propose an enhanced version of FBI, named as EFBI. The proposed EFBI seeks to reinforce communication between the investigation and pursuit teams with the aim of striking a better balance between the intensification and the diversification tasks. The performance of the proposed EFBI is compared with those of the standard FBI and some other optimization methods through three well-studied dome truss optimization problems with frequency constraints. To the best of our knowledge, this is the first time that FBI is applied to structural optimization. Results confirm that EFBI significantly outperforms the standard FBI, and has superior or comparable performance to other considered metaheuristics.

The work presents the parametric study of a steel–concrete composite beam with composite dowel connectors. The designed beam is located in a highly loaded warehouse ceiling with a useful load of 20 kN/m2. In the first part of the work, the best solution of the composite dowel beam was selected from among 7 variants. The parameterization of the composite beam was made on the basis of the following parameters determined by numerical calculations: mass of the steel part, vertical deflection of the beam, stresses in the steel and concrete, and the character of concrete cracks. Then in the second part of the work, the best variant of the beam with composite dowels was compared with the commonly used solution of a composite steel–concrete beam with headed stud connectors. In the numerical model, the finite element method was used to describe the influence of mechanical loads on the strains and stresses in the floor beam. Numerical calculations were made using the ADINA System based on FEM. A model was built from 3D-solid elements. However, the reinforcing bars were modelled with truss elements (rebar elements). The applied boundary conditions reflected the freely supported composite beam. The advanced concrete model available in the ADINA System program was used to simulate concrete, assessing the possibility of concrete cracking.

A unified approach that accounts for various buckling phenomena in truss design optimization is presented. Euler buckling of slender members, global buckling and stability of sequences of bars are all considered by optimizing the geometric nonlinear response instead of by imposing a large number of constraints. In the proposed approach, each truss member is modeled as a sequence of co-rotational beam elements with appropriate end-releases. By applying various imperfections, buckling of single truss members, unstable configurations and global buckling can be taken into account implicitly. A detailed discussion on key aspects of the proposed approach is presented, showing how the choice of imperfections highlights certain buckling types and leads to respectively stable designs. A comparison to other approaches and to results from the literature shows that the proposed approach can ensure local and global stability without actually imposing any buckling constraints. Finally, truss optimization for various levels of global deflections is presented, exposing the potential of the formulation for optimizing highly nonlinear responses.

As the static safety of mechanical structure is one of important criteria in engineering design process, it has been one of important topics to consider the static failure of a structure in topology optimization (TO). With the help of some recent relevant researches, some difficult issues in considering static failure are solved. However, this research found that the singularity issue which refers the difficulty of obtaining global optima with the KKT condition is not serious and mathematically relaxed for reinforcement TO design. And it is found that the existing qp-relaxation stress interpolation scheme to resolve the singularity issue in TO just shows the local optima issue in reinforcement TO design with different penalization factors in Solid Isotropic Material with Penalization (SIMP). In order to explain this feature, the TO problems for simple benchmark truss structures are revisited. Several two-dimensional examples only with in-plane load are solved to confirm the validity of the present study.

Strain hardening cementitious composite (SHCC) are materials exhibiting high deformation capacity and excellent crack control. In applications where SHCC is employed to enhance durability, information on the crack width and spacing under loading is important. In conventional finite element analysis, the material is commonly modeled as a continuum with tri-linear tensile behavior, which cannot capture the crack pattern. Here an efficient discrete model for SHCC is proposed to address such an issue, with the use of continuum element for matrix damage/cracking, truss element for fiber bridging effect and interface element for matrix-fiber interaction. Appropriate constitutive laws are assumed for these elements and the parameters are calibrated from direct tensile test. The validity of the model is shown by analyzing a tensile specimen and the realistic multiple cracking process of SHCC is captured. Through a systematic parametric study, the effects of important model parameters on the tensile behavior of the composites are assessed. The proposed model is further improved to accurately reproduce the evolution of crack pattern, including average and maximum crack width, crack density and crack width distribution. Efficient and accurate, the model can be used for analysis of SHCC members under bending, restrained shrinkage or subject to reflective cracking.

Truss optimization using fruit fly optimization algorithm.Advanced modelling of fruit fly food search behaviour.Efficiency in truss optimization with frequency constraints.Intuitive, few tuning parameters. A recent biological study shows that the extremely good efficiency of fruit flies in finding food, despite their small brain, emerges by two distinct stimuli: smell and visual contrast. contrast-based fruit fly optimization, presented in this paper, is for the first time mimicking this fruit fly behaviour and developing it as a means to efficiently address multi-parameter optimization problems. To assess its performance a study was carried out on ten mathematical and three truss optimization problems. The results are compared to those obtained using twelve state-of-the-art optimization algorithms and confirm its good and robust performance. A sensitivity analysis and an evaluation of its performance under parallel computing were conducted. The proposed algorithm has only a few tuning parameters, is intuitive, and multi-faceted, allowing application to complex n-dimensional design optimization problems.

Topology optimization of trusses is one of the most inviting topics in the structural optimization field. In search for the computational efficiency, researchers have implemented many algorithms for this problem. With the advent of metaheuristic algorithms, structural optimization problems have become simpler to model; however, solution of these problems remains computationally expensive. The design candidates are generated by adding and removing the members heuristically and kinematically unstable candidates are mostly eliminated in metaheuristic truss topology optimization procedures. These procedures have a major flaw that needs to be overcome; metaheuristic algorithms may discard a promising but unstable design candidate although it can be repaired by adding and/or removing a few members. This study presents an algorithm to repair kinematically unstable planar truss design candidates. The algorithm first builds the connectivity matrix of the unstable candidates and identifies the structural components through geometric decomposition. Then, the repair takes place by adding and/or removing as less members as possible systematically in the conditions as absence of a basic truss and existence of unconnected or improperly connected components, supports, forces and/or remaining members. In addition, the presented algorithm gives information on how close is a candidate to a kinematically stable configuration.

In this paper, an efficient time domain formulation is proposed for computing time history dynamic responses of 2D structures, i.e. various types of trusses and frames. Unlike the methods using frequency domain, the proposed method employs the time weighted residual approach to solve the governing differential equations of the axial and flexural wave propagation problems, directly in time. Upon choosing the time step, the solution procedure begins with expressing the variation of axial and transverse displacement components, through the member’s length, as the summations of Fourier exponential basis functions in each time step. The unknown coefficients of the next steps are computed by the implementation of recurrent relations obtained based on a pre-integration process. The equilibrium and necessary continuity conditions at the common nodes/joints of adjacent elements are also fulfilled by introducing an innovative concept utilizing source functions. The role of these source functions is to simulate the boundary effects of the axial and flexural waves propagating within the structural members, simultaneously. The efficiency of the method is demonstrated in the dynamic analysis of some samples of truss and framed structures in terms of accuracy and computational time.

The optimization of truss structures is a complex computing problem with many local minima, while metaheuristics are naturally suited to deal with multimodal problems without the need of gradient information. The Coyote Optimization Algorithm (COA) is a population-based nature-inspired metaheuristic of the swarm intelligence field for global optimization that considers the social relations of the coyote proposed to single-objective optimization. Unlike most widespread algorithms, its population is subdivided in packs and the internal social influences are designed. The COA requires a few control hyperparameters including the number of packs, the population size, and the number maximum of generations. In this paper, a modified COA (MCOA) approach based on chaotic sequences generated by Tinkerbell map to scatter and association probabilities tuning and an adaptive procedure of updating parameters related to social condition is proposed. It is then validated by four benchmark problems of structures optimization including planar 52-bar truss, spatial 72-bar truss, 120-bar dome truss and planar 200 bar-truss with discrete design variables and focus in minimization of the structure weight under the required constraints. Simulation results collected in the mentioned problems demonstrate that the proposed MCOA presented competitive solutions when compared with other state-of-the-art metaheuristic algorithms in terms of results quality.

The conventional Cellular Automata (CA) approach has the disadvantage of being particularly suited for design optimization of uniform truss ground structures with identical cells. Moreover, the conventional CA algorithms, which are intrinsically local, have to be modified in order to be able to tackle problems involving displacement constraints. This paper presents a new non-uniform Cellular Automata algorithm, which is based on non-identical cells and a modified FSD/FUD approach. The new algorithm can solve the minimum weight optimization problem of truss structures including both stress and displacement constraints. The efficiency and accuracy of the proposed methodology are proved on a number of benchmark truss design problems.

Enumerative topology is proposed, a new method for optimizing in conceptual design.An Evolution Strategy working with populations of solutions of differing lengths.Dimensional increments appear to increase consistency of optimization results. The paper describes a multiobjective optimization method aimed at supporting decisions in conceptual design. The paper identifies five characteristics to achieve this intent. One of those characteristics concerns accounting for variation configuration. The method introduces enumerative topology, a way of specifying structural configuration in terms of enumerative variables, such as the number of bays in a truss or frame. This concept is distinct from conventional topological optimization which defines configuration by specifying the presence or absence of members in a framework. The paper demonstrates the method on two benchmark problems, and then presents extended versions which incorporate enumerative topology.

Microstructure topology design method of periodic beam structure is developed.Implementation of optimization is generalized integrating commercial software.The sensitivity information is calculated with the element mutual strain energy.The method can be extended to periodic truss beam structures directly. A topology optimization method is developed for microstructure design of heterogeneous periodic beam structure aiming at its extreme or specified effective stiffness. The effective stiffness is calculated using a FEM formulation of asymptotic homogenization method for heterogeneous periodic beam. Sensitivity of stiffness to the density design variable is derived analytically based on the solution of unit cell problems under corresponding generalized strain fields. Implementation of optimization procedure is generalized to take full advantage of commercial FEM software capabilities, with several examples presented to demonstrate its effectiveness. It is shown here the proposed method is extendible to periodic truss beam design.

An aeDE is proposed for optimization of truss structures with discrete design variables.The aeDE algorithm is a newly improved adaptive version of DE with three modifications.Three improvements relate to the mutation phase, selection phase and rounding technique.The numerical results for six benchmark problems illustrate the effectiveness of aeDE. This paper proposes an adaptive elitist differential evolution (aeDE) for optimization of truss structures with discrete design variables. The aeDE algorithm is a newly improved version of the differential evolution (DE) algorithm with three modifications. Firstly, in the mutation phase, an adaptive technique based on the deviation of objective function between the best individual and the whole population in the previous generation is proposed to select a suitable mutation operator. This technique helps preserve the balance between global and local searching abilities in the DE. Secondly, in the selection phase, an elitist selection technique which helps choose the best individuals for the next generation is utilized to increase the convergence rate. Finally, a rounding technique is integrated into the aeDE for solving optimization problems with discrete design variables. The efficiency and reliability of the proposed method are demonstrated through six optimization problems of truss structures with discrete design variables. Numerical results reveal that in most of the test cases, the aeDE is more efficient than the DE and some other methods in the literature in terms of the quality of solution and convergence rate.

FSD-ES is improved to handle the displacement constraints more efficiently.The improved version follows the principles of contemporary evolution strategies.Evaluation of a kinematically unstable design is revised.Complicated truss optimization test problems are developed.The improved FSD-ES is demonstrated to outperform the best available peer methods. During the recent decade, truss optimization by meta-heuristics has gradually replaced deterministic and optimality criteria-based methods. While they may provide some advantages regarding their robustness and ability to avoid local minima, the required evaluation budget grows fast when the number of design variables is increased. This practically limits the size of the problems to which they can be applied. Furthermore, many recent stochastic optimization methods handle the size optimization only, the potential saving from which is highly limited, when compared to the most sophisticated, and obviously the most challenging scenario, simultaneous topology, shape and size (TSS) optimization. In a recent study by the authors, a method based on combination of optimality criteria and evolution strategies, called fully stressed design based on evolution strategies (FSD-ES), was proposed for TSS optimization of truss structures. FSD-ES outperformed available truss optimizers in the literature, both in efficiency and robustness. The contribution of this study is twofold. First, an improved version of FSD-ES method, called FSD-ES-II, is proposed. In comparison with the earlier version, it takes the displacement constraints in the resizing step into account and can handle constraints governed by practically used specifications. Update of strategy parameters is also revised following contemporary and new developments in evolution strategies. Second, a test suite involving a number of complicated TSS optimization problems is chosen to overcome usual shortcomings in the available benchmark problems. For each problem, performance of FSD-ES-II is compared with the best results available in the literature, often showing a significant superiority of the proposed approach.

This paper describes a generative methodology for optimum design of truss structures. The novelty of the proposed method is its combination of generative design synthesis methods with conventional gradient-based optimization and simulation models. This combination is able to achieve optimal topologies and shapes for cable trusses under various constraints: stress, displacement, stability. Furthermore, manufacturing issues properly limit the generated solutions. A graph grammar is used to define different topologies for a given load problem. The effectiveness of the method is checked by solving a variety of available test problems found in the literature as well as several new three-dimensional solutions.

Nonlinear flutter response with hysteresis loop characteristics is a special aerodynamic instability phenomenon, and is of great importance and of practical interest to long span bridge designs. This paper presents a comprehensive study on nonlinear flutter of a bridge deck that has hysteresis loop characteristics over a range of wind speeds close to the flutter onset speed, using a section model wind tunnel test and theoretical analyses. The evolutions of the hysteresis loop in both the single degree of freedom (SDOF) system in torsion and the 2 degrees of freedom (2DOF) system in the vertical direction and in torsion are studied. The formation mechanism of the hysteresis loop is discussed using the equivalent total damping as a function of vibration amplitude. Two nonlinear mathematical models for the SDOF and the 2DOF systems are proposed to predict the nonlinear flutter responses, in which both the structural and aerodynamic damping are expressed as functions of time-varying displacements. An approach is proposed to identify the aerodynamic parameters based on the displacement time histories using a harmonic balancing technique. Using the identified aerodynamic parameters, a distinct dynamic system with the same section was used to validate the accuracy of the proposed models.

In this paper a new and efficient metaheuristic algorithm is proposed for discrete performance-based seismic design optimization of steel moment frames. The proposed metaheuristic uses the Newton gradient-based method as its updating scheme in a population-based framework and therefore it is termed as Newton Metaheuristic Algorithm (NMA). In order to enable the NMA to effectively explore the discrete design space, a term containing the best solution found is added to the basic updating rule of the algorithm. In addition, a simple and efficient method is proposed in order to establish a balance between local and global search abilities of the proposed algorithm. The efficiency of the NMA is illustrated by presenting two benchmark discrete truss optimization problems. Moreover, three steel moment frames are optimized in the framework of performance-based design by the NMA and the results are compared with those of some recent metaheuristics. The performance of the algorithms is analyzed using statistical parametric and non-parametric tests indicating that NMA outperforms the other algorithms in literature.

The matrix theory for pin-jointed trusses is recalled.The role of prestress is outlined and discussed.A structural optimization process based on genetic algorithms is presented.Several cable domes are analyzed, optimized and compared. For their lightweight, versatile forms and architectural impact, cable-strut structural systems have been widely used as large span roofs of arenas, stadiums and open squares. In this paper, the matrix theory for pin-jointed trusses is firstly recalled. Then, through an elementary cable dome, the role of prestress is outlined and commented. Finally, a special optimization procedure, based on genetic algorithms, allows a thorough comparison between classical structural schemes, whose bearing capacity is due to the mechanical stiffness, and prestressed structures, whose bearing capacity is also due to the geometrical stiffness provided by the prestress.

A guided stochastic search (GSS) technique is proposed for sizing of steel frames.The principle of virtual work is utilized for handling the displacement constraints.The GSS locates promising solutions using an insignificant computational effort. Recently a design-driven heuristic approach named guided stochastic search (GSS) technique has been developed by the authors as a computationally efficient method for discrete sizing optimization of steel trusses. In this study, an extension and reformulation of the GSS technique are proposed for its application to problems from discrete sizing optimization of steel frames. In the GSS, the well-known principle of virtual work as well as the information attained in the structural analysis and design stages are used together to guide the optimization process. A design wise strategy is employed in the technique where resizing of members is performed with respect to their role in satisfying strength and displacement constraints. The performance of the GSS is investigated through optimum design of four steel frame structures according to AISC-LRFD specifications. The numerical results obtained demonstrate that the GSS can be employed as a computationally efficient design optimization tool for practical sizing optimization of steel frames.

The colliding bodies optimization (CBO), is employed for size optimization of skeletal structures.The enhanced colliding bodies optimization (ECBO) is applied to two truss and two frame structures.The capability of the CBO and ECBO are compared through four benchmark examples. The recently developed method, colliding bodies optimization (CBO), is employed for size optimization of skeletal structures. The enhanced colliding bodies optimization (ECBO) that utilizes memory to save some historically best solution and uses a random procedure to avoid local optima is also applied to skeletal structures. The capability of the CBO and ECBO are compared through two trusses and two frames structures. The design constraints of steel frames are imposed according to the provisions of LRFD-AISC. The numerical results show the successful performance of the ECBO algorithm in comparison to the CBO, and some other well-known meta-heuristics in structural optimization.

A new metaheuristic algorithm is proposed, the Search Group Algorithm (SGA).The SGA is successfully applied for the structural optimization of trusses.The SGA found the lightest structures available in the literature.The SGA outperformed the other metaheuristics in the analyzed examples. This paper presents a new metaheuristic optimization method, the Search Group Algorithm (SGA), to deal with the optimization of truss structures. The effectiveness of the SGA is demonstrated through a selection of benchmark problems taken from the literature. Special attention is given to problems that involve topology optimization, discrete design variables and/or natural frequency constraints due to the complexities that they present. As the main conclusion of these numerical experiments, the SGA was able to provide the lightest structures ever found for 5 of the 6 examples investigated, to the best of the authors' knowledge. Moreover, it was also able to improve the statistics of the independent runs of the algorithm in most cases. These results emphasize the capabilities of the SGA in this field and encourage its further development and application to real problems in engineering.

Damage-plasticity models can be used for predicting punching shear behaviour of concrete slabs.FEA results using two damage plasticity models; one implemented in FEAP and the second from ABAQUS are presented.Punching shear FE analysis is sensitive to the representation of the tensile concrete behaviour.Regularization must be adopted to avoid premature predicted failure due to localized cracking. The paper presents numerical simulations of punching shear in a reinforced concrete slab-column configuration formerly tested in the laboratory. A brief description of the test program at the University of Waterloo is reported. For the simulation, a symmetric quarter of the test configuration is employed. Full three-dimensional finite element discretized geometry is considered together with elastic-plastic reinforcement embedded as truss elements in concrete. Two regularized numerical models of concrete, formulated within elastic-plastic-damage theories, are applied. The first one, called gradient damage, is refined by an additional averaging equation where gradient enhancement involves an internal length scale. In the second one, called rate-dependent damaged plasticity model, a viscoplastic strain rate is introduced. The results for the first model implemented in FEAP and the second model from ABAQUS are discussed in detail. Different issues of numerical simulation to properly predict punching shear behaviour in the slab-column configuration are presented.

WCA and MBA are inspired by water cycle process and explosion of landmines.MBA is improved in terms of exploitation phase, so called improved MBA (IMBA).IMBA, WCA, and MBA are utilized for solving discrete sizing optimization of trusses.IMBA, WCA, and MBA outperformed other reported optimizers in terms of accuracy and computational effort. This paper presents the applications of the mine blast algorithm (MBA) and the water cycle algorithm (WCA), in addition to an improved version of MBA for weight minimization of truss structures including discrete sizing variables. The MBA mimics the explosion of landmines, while the WCA is inspired by the observation of water cycle process. An improved version of MBA (IMBA), is also presented. The efficiency of the three optimization algorithms is tested using classical benchmark discrete truss design problems. Optimization results show that MBA, IMBA, and WCA offer a good degree of competitiveness against other state-of-the-art metaheuristic techniques.

This paper implements the recently developed meta-heuristic algorithm Colliding Bodies Optimization (CBO) for the optimization of truss structures with discrete sizing variables. The CBO algorithm is inspired by the laws of one-dimensional collision. After collision of two moving bodies, with specified mass and velocity, these bodies are separated and move to new positions with new velocities. Colliding bodies correspond to candidate designs. CBO utilizes a simple formulation and does not require parameter tuning. Test problems demonstrate the efficiency of the proposed approach.

Fully Constrained Design (FCD) is a new method for discrete sizing optimization of steel structures that balances computational efficiency with solution quality for application to large-scale problems. The proposed method is based on optimality criteria, but does not require gradient information and handles discrete variables. Based on benchmarking studies, FCD produces superior quality solutions to optimality criteria (>4%), but inferior to heuristic methods (

This study investigates the application of novel computational techniques for structural performance monitoring of bridges that enable quantification of temperature-induced response during the measurement interpretation process. The goal is to support evaluation of bridge response to diurnal and seasonal changes in environmental conditions, which have widely been cited to produce significantly large deformations that exceed even the effects of live loads and damage. This paper proposes a regression-based methodology to generate numerical models, which capture the relationships between temperature distributions and structural response, from distributed measurements collected during a reference period. It compares the performance of various regression algorithms such as multiple linear regression (MLR), robust regression (RR) and support vector regression (SVR) for application within the proposed methodology. The methodology is successfully validated on measurements collected from two structures – a laboratory truss and a concrete footbridge. Results show that the methodology is capable of accurately predicting thermal response and can therefore help with interpreting measurements from continuous bridge monitoring.

This study presents a design-driven heuristic approach named guided stochastic search (GSS) technique for discrete sizing optimization of steel trusses. The method works on the basis of guiding the optimization process using the well-known principle of virtual work as well as the information collected during the structural analysis and design stages. The performance of the proposed technique is investigated through a benchmark truss instance as well as four real-size trusses sized for minimum weight according to AISC-LRFD specifications. A comparison of the numerical results obtained using the GSS with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser computational effort.

A theoretical model is presented for analysing the shear behaviour and predicting the shear strength of reinforced concrete (RC) interior beam-column joints. The model presented is referred to as the modified rotating-angle softened-truss model (MRA-STM), which is modified from the rotating-angle softened-truss model and the modified compression field theory. In the proposed methodology, the RC interior joint is treated as an RC shear panel that is subjected to vertical and horizontal shear stresses transferred from adjacent columns and beams. Employing the deep beam analogy, the characteristic strut and truss actions typical in beam-column joints are represented by the effective transverse compression stresses and the softened concrete truss in the model. Sixteen RC interior beam-column joints were subsequently analysed with the proposed model. Shear strengths of the RC interior beam-column joints predicted by the proposed model show very good agreement with the experimental results.

This paper presents an adaptation of the Dynamic Relaxation method for the form-finding of small-strain compressive structures that can be used to achieve project-specific requirements such as prescribed element lengths. Novel truss and triangle elements are developed to permit large strains in the form-finding model while anticipating the small-strain behavior of the realized structure. Forcing functions are formulated to permit element length prescription using a new iterative technique termed Prescriptive Dynamic Relaxation (PDR). Case studies of a segmental concrete shell and a pedestrian steel bridge illustrate the potential for using PDR to achieve economic and environmentally considerate structural solutions.

This paper represents a new algorithm for structural optimization with frequency constraints. The new algorithm is termed Democratic Particle Swarm Optimization. The emphasis is placed upon alleviating the premature convergence phenomenon which is believed to be one of flaws of the original PSO. When considering frequency constraints in a structural optimization problem, the search spaces happen to be highly non-linear and non-convex hyper-surfaces with numerous local optima and naturally the problem of premature convergence is amplified. The proposed algorithm is capable of coping with this problem. Four numerical examples are presented to demonstrate the viability of the algorithm.

This paper describes a new bi-level hierarchical method for optimizing the shape and member sizes of both determinate and indeterminate truss structures. The method utilizes a unique combination of algorithms that are organized hierarchically: the Fully Constrained Design (FCD) method for discrete sizing optimization is nested within SEQOPT, a gradient-based optimization method that operates on continuous shape variables. We benchmarked the method against several existing techniques using numerical examples and found that it compared favorably in terms of solution quality and computational efficiency. We also present a successful industry application of the method to demonstrate its practical benefits.

A new general formulation for the mechanical behavior of Single-Walled Carbon Nanotubes is presented. Carbon atoms are located at the nodes of an hexagonal honeycomb lattice wrapped into a cylinder. They are linked by covalent C C bonds represented by a truss or spring element, and the three-body interaction among two neighboring covalent bonds is reproduced by a rotational spring. The main advantage of our approach is to allow general load conditions (and any chirality) with no need of specific formulation for each load case, in contrast with previous works [26], [27] and [31]. Four load configurations are adopted: tension, compression, bending and torsion of cantivelered SWCNTs. Calculations with our own codes for both AMBER and Morse potential functions have been carried out, aimed to compare their final results. Initial positions of the atoms (nodes) into nanotube cylindrical geometry has been reproduced in great detail by means of a conformal mapping from the planar graphene sheet. Therefore, the effect of initial SWCNTs curvature has been introduced explicitly through a system of initial stresses (prestressed state) which contribute to maintain their circular cross-section. Numerical results and deformed shapes for nanotubes with several diameters and chiralities under each load case are used to obtain their mechanical parameters with the only objective of checking the present formulation with previous works [28], [30], [20] and [24]. Also, the significance of the atomistic discrete simulations at the nano-scale size against other continuum models is underlined.

The main contribution of the present paper is to propose an efficient hybrid optimization algorithm for layout optimization of truss structures. To achieve this, computational merits of the cellular automata (CA) and the particle swarm optimization (PSO) are integrated. In the proposed hybrid algorithm a CA-based mechanism is utilized as the velocity updating equation of the particles in the framework of the sequential unconstrained minimization techniques and therefore it is denoted as sequential cellular PSO (SCPSO). The numerical results demonstrate that SCPSO not only converges to better solutions but also provides faster convergence rate in comparison with other algorithms.

Following the principles of the state-of-the-art Evolution Strategies in continuous optimization, a novel algorithm is introduced which simultaneously optimizes shape and size of truss structures. The algorithm, called Fully Stressed Design Evolution Strategy (FSD-ES), combines advantages of the well-known deterministic approach of Fully Stressed Design and potent global search of Evolutionary Algorithms. Based on available engineering knowledge on truss analysis, a novel adaptive penalty term is also introduced and utilized to reinforce the near-bound search abilities of the algorithm. Following recent advances in empirical evaluation, the performance of FSD-ES is assessed on a reasonable test suite and compared to the best results available in the literature. Performance for the case without grouping members or exploiting symmetry are also reported which significantly increase the problem dimension, leading to more challenging test problems, more discriminating results and more reliable conclusions. Result comparison demonstrates that for more complicated problems FSD-ES reaches the same fitness noticeably faster and finds a relatively lighter structure than those previously reported in the literature.

Meta-heuristic search methods have been extensively used for optimization of truss structures over the past two decades. In this study, a new meta-heuristic search method called 'teaching-learning-based optimization' (TLBO) is applied for optimization of truss structures. The method makes use of the analogy between the learning process of learners and searching for designs to optimization problems. The TLBO consists of two phases: teacher phase and learner phase. 'Teacher phase' means learning from the teacher and 'learner phase' means learning by the interaction between learners. The validity of the method is demonstrated by the four design examples. Results obtained for the design examples revealed that although the TLBO developed slightly heavier designs than the other meta-heuristic methods in a few cases, it obtained results as good as or better than the other meta-heuristic optimization methods in terms of both the optimum solutions and the convergence capability in most cases.

The embedded through-section (ETS) strengthening method is a promising technique recently developed to increase the shear strength of deficient reinforced concrete (RC) beams. The method uses an adhesive to bond fiber-reinforced polymer (FRP) bars embedded through pre-drilled holes into the concrete core. The motivation for this work is the fact that a full understanding of the ETS technique can be achieved through finite element models. Two-dimensional finite element models have been developed to address the CFRP bar/concrete interfacial behavior of the ETS pull-out test. In the model, discrete truss elements are oriented above and below the CFRP bar to connect the bar to the two sides of the concrete. The Cosenza-Manfredi-Realfonzo (CMR) bond stress-slip model is used to represent the bond behavior. Numerical predictions show that the CFRP bar/concrete interfacial profiles are useful in determining the optimum lengths of the CFRP bars. The study has been extended to investigate FRP shear-strengthened beams using the ETS method by developing a three-dimensional finite element model. Nonlinear material behavior of the plain concrete, steel reinforcing bars and CFRP bars has been simulated using appropriate constitutive models. Results are presented in terms of ultimate load-carrying capacities, load-deflection relationships, and axial strains in the CFRP bars. The numerical predictions are compared with experimental data, and very good agreement is obtained.

This paper introduces a novel approach to truss structure shape design, drawing inspiration from biological processes, that treats each joint or member of a truss as a cell and the entire truss as a multicellular organism. The approach mimics plant tropisms in which, through cellular growth, cells change their size and shape in response to scripted gene commands. Examples illustrate the effectiveness of the approach; it is shown to produce arching and double-arching of pinned-pinned trusses, bulging of cantilever trusses and a plant-like tropic response.