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In this paper, important functional parameters of solid oxide fuel cells are identified by introducing a novel high-speed optimization method, namely adaptive chaotic grey wolf optimization algorithm. The suggested optimization method is obtained by combining the adaptive grey wolf optimization and chaotic grey wolf optimization algorithms. The chaotic algorithm is applied to the basic grey wolf optimization to achieve higher convergence speed, keep the population's diversity, and provide an initial population with uniform distribution. Besides, a nonlinear convergence factor is defined for balancing the global and local exploration abilities. Employing the improved convergence factor resulted in a new version of the grey wolf optimization algorithm, namely adaptive grey wolf optimization algorithm. Adaptive chaotic grey wolf optimization algorithm adopts the advantages of both chaotic grey wolf optimization and adaptive grey wolf optimization methods simultaneously. The adaptive grey wolf optimization algorithm is applied to a 5 kW dynamic tubular stack. The results of the simulation report the lowest values of mean squared error, higher accuracy, higher robustness, and high convergence speed for the adaptive grey wolf optimization algorithm compared to some well-known optimization methods. Besides, the proposed method shows a good agreement with experimental results with lower computational difficulty. [Display omitted] • An adaptive chaotic grey wolf optimization for parameter identification of solid oxide fuel cells is developed. • The proposed ACGWO algorithm is applied on a 5 kW tubular SOFC stack. • Various evaluation criteria and other parameter estimation techniques are discussed. • A comprehensive comparison analysis of different identification approaches is presented. • ACGWO is a competitive method in terms of accuracy, robustness, convergence and statistics. [ABSTRACT FROM AUTHOR]

To resist external pressure, stiffened spherical domes have been widely used in underwater vehicles. In traditional design of these thin-walled structures, uniform stiffeners are usually utilized and overly conservative safety factor method is employed to envelop the multi-source uncertainties mainly caused by manufacturing. In this study, a concept of non-uniformly stiffened spherical dome (NUSPD) is developed to improve the structural buckling capacity. Furthermore, an efficient reliability-based design optimization (RBDO) framework is established for NUSPD, which includes a deterministic optimization loop to fix the stiffener layout, and subsequently followed by a RBDO loop to determine the detailed stiffener dimensions and decrease the structural weight under geometric and material property uncertainties. Since the RBDO of stiffened spherical domes is very complex, an improved enhanced chaos control method together with surrogate model is proposed to improve the convergence rate. Finally, the efficiency of the proposed RBDO framework is demonstrated by the NUSPD example. [ABSTRACT FROM AUTHOR]

Abstract Reliability-based design optimization (RBDO) is a powerful tool to handle the influence of various uncertainties during optimization. However, unbearable computation cost is one of the largest barriers for its application, especially for the finite element method (FEM)-based RBDO. In this paper, an efficient and accurate RBDO framework is established based on isogeometric analysis (IGA) for complex engineering problems. Furthermore, an enhanced step length adjustment (ESLA) iterative algorithm and a second-order reliability method-based stepped-up sequential optimization and reliability assessment approach (SSORA-SORM) are proposed to boost the efficiency of RBDO. According to the situation of iteration process, the step length of search the most probable target point can be adaptively updated by the proposed criterion to improve the robustness in ESLA. In the proposed framework, the analytical first-order sensitivity is derived based on IGA in the optimization process to substitute the time-consuming finite difference method. The robustness, accuracy and efficiency of proposed methods are verified via several numerical benchmarks. Besides, three complex IGA-based examples demonstrate that the proposed method is able to save much computational cost without losing accuracy, which is inherently suitable for the RBDO of complex engineering problems. [ABSTRACT FROM AUTHOR]

The robustness and efficiency of performance measure approach (PMA) depend on the reliability loop in reliability-based design optimization (RBDO). For the reliability loop in the PMA using the minimum performance target point (MPTP) search, existing approaches can obtain stable results but may converge to inaccurate results, and higher computational efforts are required to achieve the optimum results for highly nonlinear problems. In this paper, a hybrid descent mean value (HDMV) approach is proposed based on a novel merit function, which is applied to combine the MPTP search formulas of the descent mean value (DMV) and advanced mean value (AMV). The merit function is used to adaptively control the numerical instability of the inverse reliability analysis for RBDO-based PMA. The accuracy, robustness and efficiency of the proposed DMV and HDMV methods are compared with existing methods through four nonlinear performance functions, two structural RBDO problems and a complex aircraft panel problem. The results illustrate that the DMV and HDMV methods are more robust, efficient and accurate than existing reliability methods. For the aircraft panel problem, a simultaneous buckling pattern is finally achieved by the proposed methods with better performance in terms of both convergence rate and computational efficiency. [ABSTRACT FROM AUTHOR]

For non-probabilistic reliability-based design optimization (NRBDO), existing methods cannot satisfy both efficiency and robustness requirements, especially for complex engineering problems. In this study, an efficient adaptive-loop (EAL) method for NRBDO is proposed based on an improved single loop method and enhanced chaos control method, aiming to enhance the optimization efficiency without sacrifice of numerical stability. The constraint function is reconstructed to improve the efficiency of reliability analysis. Moreover, a criteria condition is defined to guarantee the rationality of rough optimum and eliminate redundant constraints. The proposed EAL method can adaptively switch to a proper method, thus both high efficiency and robustness can be guaranteed. Nonlinear numerical examples and complex engineering problems are utilized to demonstrate the effectiveness of the proposed method by comparison with other existing methods. [ABSTRACT FROM AUTHOR]

Buckling is usually initiated from a local region near the cutout for cylindrical stiffened shells under axial compression, and then the evolution of buckling waves is governed by the combined effects of local and global stiffness, which limit the load-carrying capacity. Therefore, a simultaneous buckling pattern is crucial for improving the structural efficiency. In this study, a multi-step optimization strategy for the integrated design of near and far fields away from cutouts is proposed, and the convergence criterion of buckling optimization is improved as a deformation-based index. The numerical implementation of the asymptotic homogenization method is utilized to construct an efficient finite element model for post-buckling analysis. A 5 m diameter stiffened shell in a launch vehicle demonstrates that the proposed framework can provide a simultaneous buckling design with high structural efficiency in an efficient manner. Both the buckling deformations and stress of the optimum design are more uniform compared to other optimum designs. [ABSTRACT FROM AUTHOR]

This note presents an inverse design methodology of metal nanostructures for localized surface plasmon resonances, based on the topology optimization approach. Using the proposed method, determination of the metal distribution in nanostructures is implemented for surface enhanced Raman spectroscopy to maximize the enhancement factor. The obtained results demonstrate that the outlined approach can be used to design metal nanostructure with resonant peak and significant enhancement factor at specified incident wavelength, and to control the shift of the resonant peak by topologically optimizing the nanostructure. [ABSTRACT FROM AUTHOR]

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Abstract: Stiffened shells are very sensitive to initial imperfections, especially for geometrical imperfections. In this study, based on a 3-m-diameter orthogrid stiffened shell, post-buckling and imperfection sensitivity analyses are performed by use of explicit dynamic method. Result indicates that stiffened shell with outward hyperbolic generatrix shape shows a lower imperfection sensitivity as compared to the cylindrical one. Then, a framework of surrogate-based optimization including load-carrying capacity and imperfection sensitivity for stiffened shells is introduced, and the illustrative example demonstrates that the proposed framework has the potential to provide robust optimum design for realistic stiffened shells. [Copyright &y& Elsevier]

Abstract This paper presents an isogeometric analysis (IGA) based design method to address the stress-constrained topology optimization problem of plane stress and bending of thin plates. Based on the popular SIMP model, the integrated framework of geometry modeling, structural stress analysis and optimization is established. Owing to the geometry exactness and high-order continuity between elements, the IGA improves the computational accuracy of stress, and thus enhances the credibility of optimum design. Meanwhile, the obvious zigzag boundaries are avoided in the optimized results, and the stress function of IGA maintains the continuity for a relatively coarse discretization. Moreover, the IGA-SIMP method can easily meet the requirement of C 1 -continuity for the Kirchhoff plate formulations, which also facilitates the stress analysis and sensitivity calculation. To overcome the convergence difficulty of highly nonlinear stress aggregation constraint, two STM (stability transformation method)-based stabilization schemes combining with the P-norm function for global stress constraint are developed to achieve the stable iterations and acceptable designs. Finally, representative examples illustrate the effectiveness and convenience of the proposed approach. It is indicated that the IGA-SIMP method shows superior performance for solution accuracy and efficiency, and the local stress level is well controlled. [ABSTRACT FROM AUTHOR]

Performance measure approach (PMA) is an effective tool of the reliability-based design optimization (RBDO). And the advanced mean value (AMV) method is widely used for the evaluation of probabilistic constraint due to its simplicity and efficiency. However, the AMV method shows instability and inefficiency when applied to the concave performance measure functions, so do other existing iterative methods. In this paper, to overcome the difficulties, a modified chaos control (MCC) is applied to the AMV iterative procedure through modifying the iterative step of the chaotic dynamics analysis. Since the MCC method is inefficient for convex performance measure functions, a hybrid chaos control (HCC) method is also proposed by employing the AMV method or the MCC method adaptively during the RBDO process. Moreover, we equip PMA and sequential optimization and reliability assessment (SORA) with the HCC method for solving RBDO problems. Numerical examples are presented to demonstrate the simplicity, efficiency and robustness of the HCC method. [ABSTRACT FROM AUTHOR]

Abstract: Previously, we identified 1-(2-(4-bromophenoxy)ethoxy)-3-(4-(2-methoxyphenyl)piperazin-1-yl)propan-2-ol (1) as a novel Hsp90 inhibitor with moderate activity through virtual screening. In this study, we report the optimization process of 1. A series of analogues containing the 1-phenylpiperazine core scaffold were synthesized and evaluated. The structure–activity relationships (SAR) for these compounds was also discussed for further molecular design. This effort afforded the most active inhibitor 13f with improved activity in not only target-based level, but also cell-based level compared with the original hit 1. [Copyright &y& Elsevier]