Mixed integer multi-objective optimization of composite structures with frequency-dependent interleaved viscoelastic damping layers

Xu, Chao; Wu, Miao-Zhang; Hamdaoui, Mohamed

doi:10.1016/j.compstruc.2016.05.006

Cited by 23 publications

(14 citation statements)

References 41 publications

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“…density ρ V c = 1600 kg/m 3 and Poisson coefficient ν c = 0.5 (consult [48] for the values of the not listed constants z k and ∆ k ). A zero displacement boundary condition is imposed on the left side of the domain and four cubic cells on the middle of the right side (heavy tip mass with a material density 100 times heavier than the viscoelastic material) are not subject to optimization (see Figures 4 and 5).…”

Section: D Viscoelastic Structurementioning

confidence: 99%

Topology optimization of frequency dependent viscoelastic structures via a level-set method

Delgado

Hamdaoui

2019

Applied Mathematics and Computation

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Viscoelastic materials follow a liquid-like elastic behavior whose characteristics depend on the excitation frequency. Nowadays, this type of materials represent a high opportunity for vibration damping treatments in the automotive and aeronautic industries, for instance. This work is devoted to the application of the level-set method for topology optimization of viscoelastic structures. We look for the best distribution of viscoelastic material within a reference domain for the design of purely viscoelastic 3D damping structures and 2D viscoelastic damping treatments. In both cases one desires to maximize the structure capacity to dissipate energy measured here by the modal loss factor of the first vibration mode.

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Section: D Viscoelastic Structurementioning

confidence: 99%

Topology optimization of frequency dependent viscoelastic structures via a level-set method

Delgado

Hamdaoui

2019

Applied Mathematics and Computation

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“…Furthermore, we observe that the ROCOF is affected by both up states and mostly by the second up state. This information could be helpful in determining alert criteria associated with the deterioration of the system under study and passive vibration damping devices could be used to attenuate the vibration levels [7].…”

Section: Real Data Examplementioning

confidence: 99%

Conditional failure occurrence rates for semi-Markov chains

Votsi

2019

Journal of Applied Statistics

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In the present paper, we aim at providing plug-in-type empirical estimators that enable us to quantify the contribution of each operational or/and non-functioning state to the failures of a system described by a semi-Markov model. In the discrete time and finite state space semi-Markov framework, we study different conditional versions of an important reliability measure for random repairable systems, the failure occurrence rate based on counting processes. The aforementioned estimators are characterised by appealing asymptotic properties such as strong consistency and asymptotic normality. We further obtain detailed analytical expressions for the covariance matrices of the random vectors describing the conditional failure occurrence rates. As particular cases we present the failure occurrence rates for hidden (semi-) Markov models. We illustrate our results by means of an academic example based on simulated data. An application to real data is further presented that models sustainable vibration levels in a semi-Markov framework.Semi-Markov models (SMMs) are state-of-the-art models that are widely used in many scientific fields such as reliability and DNA analysis ([3]), seismology ([22]) etc. One of the main distinguising features of SMMs is that contrary to Markov models, they enable us to describe systems that evolve based not only on their last visited state (Markov property) but also on the time elapsed since this state. Due to this feature, popular "memory-full" distributions, such as the Weibull distribution, could be employed to describe sojourn (or interevent) times between successive events. We refer the interested reader to [8] or [12] for an introduction to homogeneous SMMs and to [18,17] for non-homogeneous SMMs, respectively.In the semi-Markov context, many reliability indicators have been introduced, including mean times to failure, hazard rates, availability functions etc. For recent advances in the topic concerning discrete time SMMs, see [1], [3], [5] and [6]. For continuous time SMMs, we address the interested reader to [10] and [11]. For advances in estimation methods of nonparametric semi-Markov models, see [15] and the references therein.Here we focus on the rate of occurrence of failures (ROCOF), which is a fundamental reliability indicator for repairable, random systems subject to multiple failures. Yeh ([23]) was

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“… and áf(p)(X,α)ñ represents the average value of the objective function over the current population, g¯j (p) is the violation of the j th constraint averaged over the current population, f(p)(XS,αS) and gj (p)(XS,αS) are the objective and constraint values with respect to the optimal continuous values XS under a given configuration αS, and all of these values will be obtained by solving the second-level approximate problem, which will be detailed in the subsection “The second-level approximate problem to optimize continuous ply thicknesses”; φ = (10/9) 0 5 . is used to enforce the 4-ply contiguity constraint, 40 and n c is the number of same-orientation plies in excess of four contiguously same orientation layers; ɛ is a small fraction of the maximum constraint to be added in the objective to discriminate between multiple designs with...…”

Section: Optimization Schemementioning

confidence: 99%

“…1 The optimum design of the laminated composite structures may lead to maximization or minimization of some of their characteristic, such as maximizing strength/stiffness, minimizing mass/deflection, or multiple objectives. 2–5 Reduction of the structural mass is a critical factor for aerospace applications, whereas it is minor factor for other aspects, like marine applications. 6 When structures are exposed to severe vibration circumstances, a frequent goal of designing such vibrating structures is to avoid resonance caused by external excitations, and natural frequency maximization, especially the fundamental one 7–9 is of great importance in the design of composite laminates to decrease the risk of resonance.…”

Section: Introductionmentioning

confidence: 99%

Maximization of fundamental frequency and buckling load for the optimal stacking sequence design of laminated composite structures

Chen

2018

Proceedings of the IMechE

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The paper illustrates the application of a two-level approximation method to the lay-up design of laminated structures for maximization of fundamental frequency and buckling load with design constraints. Previously developed for the mass-minimization design, the approximation method was achieved by starting from an initial design of stacking sequence. Benchmark examples have verified its efficacy in dealing with the mass-reduction problems, but it does not have the capability to address the objective-maximization problems, which is mainly due to the limitation of the second-level approximate problem. In this work, this method is improved and extended for the consideration of objective maximization with more design constraints. The second-level approximate problem is reconstructed with mixed direct/reciprocal design variables, suitable for solving maximization problems. By varying different initial designs of stacking sequence and conducting repeated runs in the numerical examples, its efficiency is significantly shown after making comparisons with other methods.

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Mixed integer multi-objective optimization of composite structures with frequency-dependent interleaved viscoelastic damping layers

Cited by 23 publications

References 41 publications

Topology optimization of frequency dependent viscoelastic structures via a level-set method

Topology optimization of frequency dependent viscoelastic structures via a level-set method

Conditional failure occurrence rates for semi-Markov chains

Maximization of fundamental frequency and buckling load for the optimal stacking sequence design of laminated composite structures

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