A new view for the analytical formulation of torsional ultimate strength for reinforced concrete (RC) beams by experimental data is explored by using a new hybrid regression method termed Evolutionary Polynomial Regression (EPR). In the case of torsion in RC elements, the poor assumptions in physical models often result into poor agreement with experimental results. Nonetheless, existing models have simple and compact mathematical expressions since they are used by practitioners as building codes provisions. EPR combines the best features of conventional numerical regression techniques with the effectiveness of genetic programming for constructing symbolic expressions of regression models. The EPR modeling paradigm allows to figure out existing patterns in recorded data in terms of compact mathematical expressions, according to the available physical knowledge on the phenomenon (if any). The procedure output is represented by different formulae to predict torsional strength of RC beam. The multi-objective search paradigm used by EPR allows developing a set of formulae showing different complexity of mathematical expressions as resulting into different agreement with experimental data. The efficiency of such approach is tested using experimental data of 64 rectangular RC beams reported in technical literature. The input parameters affecting the torsional strength were selected as cross-sectional area of beams, cross-sectional area of one-leg of closed stirrup, spacing of stirrups, area of longitudinal reinforcement, yield strength of stirrup and longitudinal reinforcement, concrete compressive strength. Those results are finally compared with previous studies and existing building codes for a complete comparison considering formulation complexity and experimental data fitting. © 2011 Elsevier Ltd. All rights reserved.

The study presented in this paper is focused on an analytical method for constructing fragility curves of a given class of existing structures, based on a stochastic approach and which makes use of the Hazus database. The analysed structure is a non-linear one degree of freedom (SDoF) system: its constitutive law is described by means of a hysteretic model, whose parameters are obtained by an identification procedure starting from the Hazus data. A particular class of structures, the essential facilities, are analyzed. The system's response to seismic action, here modelled by means of the modulated Clough and Penzien filtered stochastic process, is obtained by using the stochastic linearization technique and the covariance analysis. In order to develop the fragility curves, a displacement based damage index is adopted and, finally, fragility curves are obtained in terms of the probability of exceeding a given damage level, by using an approximate theory of stochastic processes. The main innovation of the proposed approach is that it can be directly extended to other kinds of structures which are not included in the Hazus database, since the procedure requires only the knowledge of the capacity curve, which can be obtained by standard procedures.

In this work a comparative analysis between different optimization criteria is performed for a linear Tuned Mass Damper (TMD) devices problem. Optimal TMD mechanical parameters are evaluated considering a simple one degree-of-freedom system subject to a base acceleration modeled as a stationary filtered stochastic process. Whereas common TMD optimization methods consider only TMD frequency and damping ratio as design variables, in this study a complete approach will be proposed, which takes into account also the TMD mass as design variable. The effectiveness of the vibration control strategy is evaluated expressing the objective function in terms of two different reduction factors of the system response: the displacement and the inertial acceleration, respectively. The mechanical characteristics of the TMD, frequency ratio, damping ration and mass ratio, represent the design variables of the optimization problem. This is carried out numerically and then various analyses of sensitivity are developed by varying the input and structural parameters in order to assess the efficiency of the TMD strategy under different input and mechanical configurations. Variations between different criteria are also evaluated.

Optimization is a central aspect of structural engineering, but its practical application hasn't been supported by mathematical and numerical tools because of inner strong non-linear aspects involved. Moreover during last few decades Evolutionary Algorithms (EAs) gives new interest and horizons in this specific topic, thanks to their strong capacity in treatment of these problems more efficiently than standard methods. But a common criticism to EAs is lack of efficiency and robustness in handling constraints, mainly because they were originally developed for unconstraint problems only. For this reason during past decade hy-brid algorithms combining evolutionary computation and constraint-handling techniques have shown to be effective in this specific area. Moreover still now this is a crucial point for practical applications in structural optimization. In this paper a Normalized Domination Se-lection-based (NDS) rule is proposed to solve constrained-handling optimization problems using a modified version of proposed Differential Evolution algorithm (NDS - DEa). The strategy developed doesn't requires any additional parameter, increasing the appeal for a simple implementation in many real problems by structural designer without a specific know-ledge in the field. Mainly it is based on a domination criteria in selection phase. Actually a common way for constrained handling is introducing a specific role for selection step, so that all other phase of EA aren't modified; in this way DE flow chart scheme doesn't present any modification from a standard unconstrained one. Anyway the specific constrained selection scheme plays an important role in solution search efficiency, certainly more than in unconstrained cases. Unconstrained selection is based only on comparing individuals OF values, but in constrained one it seemed somewhat different and complicated. The more simple, common and intuitive way for approaching this phase is the penalty function, where OF values are reduced for those individuals don't satisfying constraints disqualifies (unfeasible in-dividuals). It is immediate (and well known in literature) that depending on penalty low adopted, a more drastic or permissive surviving of unfeasible solutions happened. But this is a central point in this problems, because of in many cases indeed real optimal solutions lies just on one constraints, so that its correct evaluation needs of specific research around the boundary, not only in the feasible space. to develop this strategy the domination concept is related to the specific selection that has to be implemented. If in a unconstrained contest it means simply that the domination coincide with the OF ranking, in the constrained contest the question has to be properly treated. In fact there are three possible scenarios: ->both two individuals are feasible -> selection based on rank -> both two individuals are unfeasible -> selection of the feasible one -> one is feasible and the other is unfeasible

The objective of a base isolation system is to decouple the building from the damaging components of the earthquake by placing isolators between the superstructure and the foundation. The correct identification of these devices is, therefore, a critical step towards reliable simulations of base-isolated systems subjected to dynamic ground motion. In this perspective, the parametric identification of seismic isolators from experimental dynamic tests is here addressed. In doing so, the focus is on identifying Bouc-Wen model parameters by means of particle swarm optimization and differential evolution. This paper is especially concerned with the assessment of these non-classical parametric identification techniques using a standardized experimental protocol to set out the dynamic loading conditions. A critical review of the obtained outputs demonstrates that particle swarm optimization and differential evolution can be effectively exploited for the parametric identification of seismic isolators.

Passive strategies based on the introduction of energy dissipating devices into the structures have received considerable attention in recent years. Within this framework, as re-liable and cheap energy-dissipation devices, viscous fluid dampers have been largely used in seismic protection of industrial machines, technical equipments, buildings and bridges. Since the versatility of this passive protection system satisfactorily meets a wide range of require-ments, a reliable identification of their nonlinear mechanical behavior is of outstanding im-portance. This paper focuses on the parametric identification of fractional derivative based models for nonlinear viscous dampers by means of non-classical methods, which are uncon-ventional algorithms whose inner work is based on socially, physically and/or biologically inspired paradigms. Non-classical strategies are potentially powerful tools for solving com-plex identification problems because of their start-point independence, noise robustness and the capability in looking for the best solution in a global way. In contrast, it is important to highlight that they typically possess weak forms of convergence. For better assessing the cor-rectness of some non-classical methods in parametric identification of viscous dampers, we perform a large comparative analysis which involve the following soft computing based tech-niques: a multi-species genetic algorithm, six standard differential evolution algorithms and four swarm intelligence based algorithms (including a chaotic particle swarm optimization algorithm). A numerical study is initially conducted in order to investigate the general relia-bility of these methods. Moreover, the paper also provides some results about the parametric identification of nonlinear viscous dampers by using experimental data. A critical review of the obtained evidences is given in order to provide useful guidelines for similar engineering applications.

This paper is concerned with modeling earthquake-induced ground accelerations and the simulation of the dynamic response of linear structures through the principles of stochastic dynamics. A fully evolutionary approach, with nonstationarity both in amplitude and in frequency content, is proposed in order to define the seismic action, based on seismological information in the form of a small number of input parameters commonly available in deterministic or probabilistic seismic design situations. The signal is obtained by filtering a Gaussian white-noise. The finite duration and time-varying amplitude properties are obtained by using a suitable envelope function. By utilizing a subset of the records from the PEER-NGA strong-motion database, and time-series analysis tools extended to nonstationary processes, the key transfer-function properties, in terms of circular frequency, damping ratio and spectral intensity factor, are identified. A regression analysis is conducted for practical and flexible application of this model, in order to empirically relate the identified time-varying parameters of the filter to the characteristics defining earthquake scenarios such as magnitude, rupture distance and soil type. A validation study and a parametric investigation using elastic response spectra is also included. Results show that the final seismic model can reproduce, with satisfactory accuracy, the characteristics of acceleration records in a region, over a broad range of response periods.

A modified real-coded genetic algorithm to identify the parameters of large structural systems subject to the dynamic loads is presented in this article. The proposed algorithm utilizes several subpopulations and a migration operator with a ring topology is periodically performed to allow the interaction between them. For each subpopulation, a specialized medley of recent genetic operators (crossover and mutation) has been adopted and is briefly discussed. The final algorithm includes a novel operator based on the auto-adaptive asexual reproduction of the best individual in the current subpopulation. This latter is introduced to avoid a long stagnation at the start of the evolutionary process due to insufficient exploration as well as to attempt an improved local exploration around the current best solution at the end of the search. Moreover, a search space reduction technique is performed to improve, both convergence speed and final accuracy, allowing a genetic-based search within a reduced region of the initial feasible domain. This numerical technique has been used to identify two shear-type mechanical systems with 10 and 30 degrees-of-freedom, assuming as unknown parameters the mass, the stiffness, and the damping coefficients. The identification will be conducted starting from some noisy acceleration signals to verify, both the computational effectiveness and the accuracy of the proposed optimizer in presence of high noise-to-signal ratio. A critical and detailed analysis of the results is presented to investigate the inner work of the optimizer. Finally, its performances are examined and compared to the most recent results documented in the current literature to demonstrate the numerical competitiveness of the proposed strategy.

The optimum design of tuned liquid column damper (TLCD) is usually performed by minimizing the maximum response of structure subjected to stochastic earthquake load without imposing any restrictions on the possible maximum oscillation of the liquid within the vertical column. However, during strong earthquake motion, the maximum oscillation of vertical column of liquid may be equal to or greater than that of the container pipe. Consequently the physical behavior of the hydraulic system may change largely reducing its efficiency. The present study deals with the optimization of TLCD parameters to minimize the vibration effect of structures addressing the limitation on such excessive liquid displacement. This refers to the design of optimum TLCD system which not only assure maximum possible performance in terms of vibration mitigation, but also simultaneously put due importance to the natural constrained criterion of excessive lowering of liquid in the vertical column of TLCD. The constraint is imposed by limiting the maximum displacement of the liquid to the vertical height of the container. Numerical study is performed to elucidate the effect of constraint condition on the optimum parameters and overall performance of TLCD system of protection.

The tuned liquid column dampers (TLCDs) have been shown to be effective vibration control devices for flexible structures subjected to long-duration, periodic or harmonic excitations. Their potential applications for seismic protection and retrofitting were recently explored. The optimum TLCD parameters are normally obtained based on the implicit assumption that the involved variables are deterministic. However, it is well known that the efficiency of TLCDs may be jeopardized if its parameters are not properly tuned to the vibrating mode of interest, for instance as consequence of the unavoidable presence of uncertain variables. Thus, the optimization of damper parameters considering model uncertainties has attracted a great deal of interest. The robust design of TLCDs for the passive control of mechanical systems under random ground motion is investigated in the present paper by coupling random vibration analysis and credibility theory in order to take into account fuzzy uncertainties. In doing so, two antithetical objective functions are considered, and they are the expected value and the variance of an appropriate displacement-based fuzzy structural index. Specifically, this latter one is introduced to characterize the performance variability due to the existence of fuzzy uncertainties affecting, both the system and random loading parameters. A numerical study is performed to demonstrate the applicability of the developed approach.

The paper addresses the lateral-torsional buckling for a special steel truss structure which is adopted to reinforce a particular class of composite steel-concrete beams. The investigated instability phenomenon deals with a transitory ultimate limit state that may occur when the truss structure is being assembled and is bearing the precast floor system, before the concrete has hardened. During this transitory stage the truss beam works as a steel structure and may exhibit local or global instability phenomena. It provides the reinforcement of the final composite steel-concrete beam once the concrete has hardened. The main result of this paper is an analytical approach for the estimation of the elastic critical moment which is required to calculate the final design lateral-torsional buckling resistance moment in accordance with the technical code in force (the European standard for steel structures is considered in this paper). The simplified analysis this paper presents leads to a closed-form solution for the elastic critical moment, thus providing a simple and rapid tool for the calculation of the lateral-torsional buckling resistance moment. A comparison to a finite element analysis has been performed to demonstrate the correctness of the proposed analytical formulation

A concrete sub-base layer with pretreated recycled rubber from discarded tyres (PFU), is described.