1,387 research outputs found
Robust optimum criteria for tuned mass dampers in fuzzy environments
No full textTuned mass dampers are widely adopted passive strategies for vibrations mitigation, in the past years extensively investigated to improve the offered protection level in any mechanical systems in which they are installed. Although different mechanical and energetic optimum criteria have been proposed in the last decades by assuming involved parameters as deterministically known, nowadays the need persists to explore more realistic approaches for virtue of the unavoidable presence of uncertain variables. In fact, deterministic-based optimum criteria often lead to incorrect design, evidently because it is an excessive oversimplification and heavily in conflict with practical circumstances. Consequently, searching for robustness-based criteria in the optimal design for this class of mechanical devices is a crucial question. In order to define a collection of solutions able to ensure an acceptable trade-off between mechanical performances and immunity against the variability of the involved parameters, robust-based design optimization is an important and alternative way for supporting design process. Typically, methods proposed until now are based on the probabilistic description of the uncertain variables and only few approaches consider uncertainties in both system and loads. In this paper, robust-based design optimization problems for tuned mass dampers are formulated and resolved in view of fuzzy environments. The antithetical objective functions of the problems are defined within the framework of the credibility theory: the first one is the fuzzy expected value of the adopted performance-based structural index, the second one is its fuzzy variance. Specifically, this latter is introduced to characterize the performance variability due to the existence of uncertain variables. In our analysis, protected systems are assumed subject to random vibrations, in the aim to extend the applicability of the proposed methodology to different and general (natural or artificial) dynamic loads. Both models for structural systems and dynamic loads include fuzzy variables, in order to take into account also epistemic uncertainties. Finally, several numerical applications are presented to investigate the practical utility of the obtained results
Genetic-algorithm-based strategies for dynamic identification of nonlinear systems with noise-corrupted response
No full textThe main objective of this paper is to investigate efficiency and correctness of different real-coded genetic algorithms and identification criteria in nonlinear system identification within the framework of non-classical identification techniques. Two conventional genetic algorithms have been used, standard genetic algorithm and microgenetic algorithm. Moreover, an advanced multispecies genetic algorithm has been proposed: it combines an adaptive rebirth operator, a migration strategy, and a search space reduction technique. Initially, a critical analysis has been conducted on these soft computing strategies to provide some guidelines for similar engineering and physical applications. Therefore, the hysteretic Bouc-Wen model has been numerically investigated to achieve three main results. First, the computational effectiveness and accuracy of the proposed strategy are checked to show that the proposed optimizer outperforms the aforementioned conventional genetic algorithms. Secondarily, a comparative study is performed to show that an improved performance can be obtained by using the Hilbert transform-based acceleration envelope as objective function in the optimization problem (instead of the pure acceleration response). Finally, system identification is conducted by making use of the proposed optimizer to verify its substantial noise-insensitive property also in the presence of high noise-to-signal ratio. © 2010 ASCE
Parameters identification of Van der Pol-Duffing oscillators via particle swarm optimization and differential evolution
No full textMany of the proposed approaches for non-linear systems control are developed under the assumption that all involved parameters are known in advance. Unfortunately, their estimation is not so simple because the nature of the non-linear behaviors is very complex in the most part of the cases.
In view of this complication, parameters identification of non-linear oscillators has attracted increasing interests in various research fields: from a pure mathematical point-of-view, parameters identification can be formalized as a multi-dimensional optimization problem, typically over real bounded domains. In doing this, the use of the so-called non-classical methods based on soft computing theories seems to be promising because they do not require a priori information and the robustness of the identification against the noise contamination is satisfactory. However, further studies are required to evaluate the general effectiveness of these methodologies. In this sense, the paper addresses the consistency of two classes of soft computing based methods for the identification of Van der Pol–Duffing oscillators. A large numerical investigation has been conducted to evaluate the performances of six differential evolution algorithms (including a modified differential evolution algorithm proposed by the authors) and four swarm intelligence based algorithms (including a chaotic particle swarm optimization algorithm). Single well, double well and double-hump oscillators are identified and noisy system responses are considered in order to evaluate the robustness of the identification processes. The investigated soft computing techniques behave very well and thus they are suitable for practical applications
A new possibilistic reliability index definition
No full textIn this work, a new and efficient definition for a reliability index is explored for real structural engineering problems. The main innovative aspect is that it is based on a possibilistic criteria instead of a probabilistic one. Its definition deals with engineering cases where uncertain parameters of basic structural reliability problems can be operatively treated as fuzzy variables. A fuzzy-based version of classic Cornell proposed reliability index is discussed. Consequently, differences and advantages with respect to other non-probabilistic reliability measures reported in literature are critically analyzed with reference to well-specified criterions. Finally, two numerical examples are illustrated. The first, in the framework of the materials strength problem, is a simple comparison between these fuzzy reliability indicators, and is developed to clarify the applicability of our proposal. Subsequently, another more realistic numerical example is proposed; it is developed to appreciate its effectiveness in reliability assessment of complex structural systems
Sensitività della resistenza a compressione del calcestruzzo all’incertezza del rapporto acqua-cemento
No full textNon-stationary stochastic modulation function definition based on process energy release
No full textMany real physical events are characterized by a random nature, as for earthquakes, sea waves, wind pressure, sea waves and so on. A common way to define these events is to think them as a realization of a stochastic process, and the simplest way to model them is to adopt stationary processes characterized mainly by their frequency contents. However, sometime it is necessary to consider also their evolutionary nature in the time, in order to properly take into account the non-stationary nature, as in case of seismic records. In these circumstances, a common mathematical approach is to assume the process as a non-stationary separable one, and then a key problem is to define appropriately a modulation function able to represent the time variation of the physical event. This paper purposes a method based on the energy release velocity definition of the modulation function with the aim to represent time intensity evolution of real non-stationary phenomena. With this scope, the envelope function is assumed related to the manner in which the input energy is built-up over time. Using the Iwan and Hou mathematical formulation, the procedure defines modulation function parameters in a consistent way with excitation input energy evolution. Finally, a closed formulation is obtained to set up the modulation function coherently with the energy release velocity of a single record, or of the mean value of a class of records. An example based on a real seismic event shows the effectiveness of the proposed method
Sensitività della resistenza a compressione del calcestruzzo all’incertezza del rapporto acqua-cemento delle miscele
No full textOptimum design of prestressed concrete beams using constrained differential evolution algorithm
No full textThis paper is concerned with the cost minimization of prestressed concrete beams using a special differential evolution-based technique. The optimum design is posed as single-objective optimization problem in presence of constraints formulated in accordance with the current European building code. The design variables include geometrical dimensions that define the shape of the cross section and the amount of prestressing steel. A special (μ + λ)-constrained differential evolution method is performed in order to solve the optimization problem. Its search mechanism depends on several mutation strategies whereas an archiving-based adaptive tradeoff model is in charge of selecting a specific constraint-handling technique. Finally, numerical examples are included to illustrate the application of the presented approach
Fuzzy-based robust structural optimization
No full textRobust optimization is conventionally defined as the collection of the possible problem solutions that can ensure acceptable performances and sufficient immunity against the effects of uncertain parameter variability. Methods proposed until now use a probabilistic way to model uncertainty and to quantify the final sensitivity. In this work, a fuzzy uncertainty modellization is adopted for structural engineering. In particular, to define solution performance scattering, the fuzzy entropy is used as a global measure of variable dispersion. The final formulation of the problem deals with two antithetical objective functions, the fuzzy expected value of structural performance and its fuzzy entropy. This fuzzy-based approach in robust design is able to give a set of Pareto optimal solutions in terms of structural efficiency and sensitivities regarding uncertainty, and represents a suitable tool in supporting the decision maker. Finally, different applications have been developed to demonstrate the applicability of the proposed method
Fuzzy Time-Dependent Reliability Analysis of RC Beams Subject to Pitting Corrosion
No full textSteel bars pitting corrosion is an electrochemical process that could seriously jeopardize the reliability of reinforced concrete structures. Even if detailed models exist to predict the lifetime of the concrete element when it is subject to this environmental attack, their applications present serious limitations that undergo, to the noteworthy sources of, uncertainty of many problem parameters. This restriction could produce erroneous solutions, especially when analysis deals with existing buildings or little information about problem parameters are accessible. In detail this takes place when real environmental conditions, mechanical properties as well as load conditions, could only be estimated and not known with enough accuracy. To overcome this problem, some methodologies have been developed, assuming that uncertainty variables can be suitably modeled in a probabilistic way, and therefore traditional theories for reliability assessment can be used. Nonetheless, in the analysis of this problem, there are other parameters that cannot be treated opportunely in a probabilistic way. The main purpose of this paper is to develop an efficient alternative approach for time-dependent reliability analysis regarding reinforced concrete beams subject to pitting corrosion, when probabilistic and nonprobabilistic parameters occur at the same time. With this new approach, it is possible to obtain a versatile tool to support the decision maker in planning maintenance interventions
- …
