English

The performance of a new implementation of the augmented Lagrangian method is evaluated on a range of explicit and structural sizing optimization problems. The results are compared with those obtained using other mathematical programming methods. The implementation uses a first-order Lagrange multiplier update and the Hessian of the augmented Lagrangian function is approximated using partitioned secant updating. A number of different secant updates are evaluated. The results show the formulation to be superior to other implementations of augmented Lagrangian methods reported in the literature and that, under certain conditions, the method approaches the performance of the state-of-the-art SQP and SAM methods. Of the secant updates, the symmetric-rank-one update, is superior to the other updates including the BFGS scheme. It is suggested that the individual function, secant updating employed may be usefully applied in contexts where structural analysis and optimization are performed simultaneously, as in the simultaneous analysis and design method. In such cases the functions are partially separable and the associated Hessians are of low rank.

Recent advances in the field of control theory have enabled us to design active vibration control systems for various structures. In many studies, the controller used to suppress vibration has been synthesized for the given mathematical model of structure. In these cases, the designer has not been able to utilize the degree of freedom to adjust the structural parameters of the control object. To overcome this problem, so called “Structure/ Control Simultaneous Optimization Method” is used. In this context of view, this paper is concerned with the active vibration control of bridge towers, platforms and ocean vehicles etc. Simultaneous design method is used to achieve optimal system performance. Here, a general framework for the simultaneous design problem of output feedback case is introduced based on LMI (Linear Matrix Inequality). The simulation results show that the proposed design method achieves desirable control performance.

In the frame of an investigation about surrogate models employed in aerodynamic optimization problems, this work aims at illustrating the suitability of adapted design space sampling to evolutionary optimization. The adaptive sampling algorithm is based on the Weighted Expected Improvement idea applied to a Kriging-based meta-model. A multipoint airfoil optimization is set as test case. A deep investigation is devoted to the tuning of the weights of Expected Improvement function to enhance the performance of the optimization process. A comparison between a pure genetic optimization and a Weighted Expected Improvement approach is proposed. Efficiency and quality of the obtained results are discussed.

This paper proposes a new integrated design method to simultaneously optimize the coupled structural parameters and controllers of mechanical systems by combining decentralized control techniques and Riccati-based control theories. The proposed integrated design method aims at minimizing the closed-loop H2 norm from the disturbance to the system cost. In this paper, the integrated design problems have been formulated in the cases of full state-feedback controllers and full order output-feedback controllers. We extend the current linear time invariant (LTI) control system to a more general framework suitable for the needs of integrated design, where the structural design is treated as a passive control optimization tackled by decentralized control techniques with static output feedback, while the active controller is optimized by solving modified Riccati equations. By using this dual-loop control system framework, the original integrated design problem is transferred to a constrained structural design problem with some additional Riccati-equation based constraints simultaneously integrating the controller synthesis. This reduces the independent design variables from the structural design parameters and the parameters of the controller to the structural design parameters only. As a result, the optimization efficiency is significantly improved. Then the constrained structural design problem is reformed as an unconstrained optimization problem by introducing Lagrange multipliers and a Lagrange function. The corresponding optimal conditions for the integrated design are also derived, which can be efficiently solved by gradient-based optimization algorithms. Later, two design examples, an active–passive vehicle suspension system and an active–passive tuned mass damper (TMD) system, are presented. The improvement of the overall system performance is also presented in comparison with conventional design methods.

This article describes the aerodynamic coupling modelling problem and autopilot design method of highly manoeuvring skid-to-turn missiles. A well-defined linearized aerodynamic model of flight vehicle is necessary to design high-performance flight control system. Especially, in the case of missile with high angle of attack and large aerodynamic coupling effect, a linearized model used for the flight control system design plays an important role in determining the stability and performance of the overall system. Also, the partial derivatives of aerodynamic coefficients being used to derive the linearized model represent the primary characteristics that determine the stability of the control system. In this article, the calculation method of aerodynamic derivatives and autopilot design method which reflects the coupling effects of highly manoeuvrable missiles is proposed. First, two different calculation methods of aerodynamic derivatives are suggested. Also, the strength and weakness of each method are analysed. Also, it is explained that the calculation method of aerodynamic derivatives using the alpha–beta constant method is more reasonable than bank constant method for highly manoeuvrable missiles with severe coupling effects. In this case, the effective autopilot design approach is to directly apply the control schemes for multi-input multi-output systems. The suggested method is applied to the derivation of linearized aerodynamic coupling model for skid-to-turn missile which has heavy aerodynamic coupling due to high manoeuvrability. For validation of the suggested model, the autopilot design processes for a generic surface-to-air missile are performed. Non-linear simulation results are given to show that the proposed modelling method reflects the motion characteristics of non-linear missile system. In order to improve the performance of autopilot, the autopilot implementation procedures using the online gain calculation scheme are also discussed briefly.

In this research two comparative studies are conducted in application to the concurrent design optimization method of Simulta neous ANalysis and Design (SAND) In one study three different forms of equality constraints referred to as compatibility constraints in the SAND procedure are compared with respect to their impact on algorithm efficiency. Results indicate that the form of the compatibility con straints can have a significant impact on performance in the SAND based procedure. In a second study a Generalized Reduced Gradient (GRG) optimizer and a Sequential Quadratic Programming (SQP) optimizer are compared with respect to their efficacy as the internal opti mizer within the SAND based optimization procedure. Comparative studies indicate that the SQP method is preferred over the GRG method in application of SAND based design. The comparative studies were conducted in application to two Multidisciplinary Design Optimization (MDO) test problems. The method of SAND was originally developed as an optimization strategy for structural design problems. Recent studies have focussed on applying the principles of SAND to multidisciplinary design environments In this research we focus on the concurrency that can be achieved in multidisciplinary design environments using SAND. In a multidisciplinary design environment the SAND approach facilitates each of the seven principles of concurrent engineering as described in Prasad, 1996. The SAND based method provides for: parallel work groups, parallel product decomposition, concurrent resource scheduling, concurrent processing, minimal interfaces, transparent communi cation and quick processing. Application studies confirm that a significant savings in the number of analyses required for design optimiza tion are observed when using the SAND approach of concurrent design. SAND based design delivers on the promise of concurrent engi neering, namely to develop optimal designs, working concurrently, while reducing design cycle time.

Solving CFD inverse problems dealing with complex aerodynamic configurations like multi-element airfoils remains a difficult and expensive procedure, which requires seamless interfacing between several softwares like computer-aided design (CAD) system, mesh generator, flow analyzer, and an optimizer. It is essential to ensure the mesh quality during the optimization procedure for maintaining an accurate design. A fast meshless method using second and fourth order artificial dissipations and dynamic clouds of points based on the Delaunay graph mapping strategy is introduced to solve inverse computational fluid dynamics problems. The purpose of this paper is to use genetic algorithms and Nash genetic algorithms for position reconstructions of oscillating airfoils. The main feature of this paper is a detailed investigation on inverse problems in aerodynamics using both flexibility and efficiency of the fast meshless method. Comparisons of prescribed and computed aerodynamics parameters are presented for position reconstruction problems in aerodynamic design using both the fast meshless method coupled with artificial dissipation and a finite volume method. Numerical results are presented to illustrate the potential of the fast meshless method coupled with artificial dissipation and evolutionary algorithms, to solve more complex optimization problems of industrial interest occurring in multidisciplinary design.

Shape morphing of laminated composite structures with photostrictive actuators via topology optimization

Two and three level VSC inverters are the building blocks of most of inverter applications necessitating the employment of appropriate switching techniques that result in harmonic free sinusoidal output. The paper presents the generalized method for harmonic elimination in two and three level voltage sourced converter. The technique used for suppression of selective low-ordered harmonics form the inverter's output voltage waveform is Selective harmonic elimination (SHE). The inverter's output voltage waveform is mathematically modeled using Fourier series that results in the system of nonlinear equations. The non-linear equations are solved for eliminating the specific low order harmonics. The main objective in calculating appropriate switching angle is to minimize the value of Total Harmonic Distortion (THD). To solve the system of non-linear equations numerical method Newton Raphson is applied and appropriate switching angles are calculated. The remaining uneliminated higher order harmonics are eliminated by connecting appropriate value of filter at the output stage of VSC inverter. The model of two level VSC is simulated in SimPowerSystem Matlab tool bar together with the algorithm of Newton Raphson technique. The time domain plot and frequency spectrum of inverter's output waveform is presented in the results section. The results of two and three level VSC inverters are analyzed and debated together with the comparative analysis on the basis of THD. Moreover, a comparison is presented on the basis of IEEE standard Std. 519 and EN 50160.

Design method for relief well trajectory to avoid side-track operations and control the relative distance

In this investigation, a decomposition approach is employed for reliability-based design optimization of multidisciplinary systems. In the last few years, a variety of different approaches for reliability-based design optimization have been proposed in the literature. Traditionally, reliability-based design optimization is formulated as a nested optimization problem, where the inner loop, generally involves the solution to an optimization problem for computing the probability of failure corresponding to the failure modes. Such a formulation is by nature computationally intensive, requiring a large numbers of function and constraint evaluations. To alleviate this problem, researchers have developed single level reliability-based optimization formulations. The single level approach is expensive for multidisciplinary systems because of the fact that the complex coupled nature of multidisciplinary systems are likewise computationally intensive requiring iterative solvers. To reduce the computational effort of performing reliability-based design optimization in application to multidisciplinary systems, a decomposition approach for optimization is employed. The method of Simultaneous ANalysis and Design (SAND) is employed as an optimization driver within a single level reliability-based design optimization strategy. The methodology is illustrated in application to multidisciplinary test problems.

In this paper, we present a scalable parallel framework, which employs grid computing technologies, for solving computationally expensive and intractable design problems. Using an aerodynamic airfoil design optimization problem as an example the application of the grid computing strategies is discussed.

This paper discusses the influence of different Radial Basis Function (RBF) in metamodel construction to be applied to 3D aerodynamic wing optimization problems using the Constrained Optimization with Response Surface (CORS) methodology in conjunction with a stochastic Controlled Random Search Algorithm (CRSA). CORS methodology is based on the iterative construction and optimization of response surfaces with a robust search pattern application. In the CORS methodology the response surface may be generate by at least three types of methods: (i) Classical (polynomials and parametric surfaces), (ii) Statistical (K-Nearest, Kriging and Gaussian Processes) and (iii) Advanced (RBF and Neural Network). The response surfaces used in this paper are constructed using six different types of RBF: Gaussian, Hardy’s Multiquadric and Inverse Multiquadric, which depend on a shape parameter, and linear, cubic and thin plate spline, which do not depend on a shape parameter. The RBF’s are directly applied on the response surface construction inside the CORS structure. Thus the choice of a RBF and of a shape parameter (being the case) may influence significantly the methodology efficiency. The CORS methodology is here applied for accelerating the optimization process of wing aerodynamic designs with a solver based on a first order 3D panel method and a 2D boundary layer model. Since the main objective of this paper is of prospective nature, the choice of a relatively low-fidelity flow computation solver is justified. One considers problems of minimizing the aerodynamic coefficient relation (CD/CL) and the inverse of lift coefficient (1/CL). Comparative influence of the RBF choice on the acceleration induced by CORS methodology is investigated taking into account the number of expensive objective function evaluations necessary to find the minimum value in each problem.

PurposeAerodynamic shape optimisation is a complex problem usually governed by transonic non-linear aerodynamics, a high dimensional design space and high computational cost. Consequently, the use of a numerical simulation approach can become prohibitive for some applications. This paper aims to propose a computationally efficient multi-fidelity method for the optimisation of two-dimensional axisymmetric aero-engine nacelles.Design/methodology/approachThe nacelle optimisation approach combines a gradient-free algorithm with a multi-fidelity surrogate model. Machine learning based on artificial neural networks (ANN) is used as the modelling technique because of its ability to handle non-linear behaviour. The multi-fidelity method combines Reynolds-averaged Navier Stokes and Euler CFD calculations as high- and low-fidelity, respectively.FindingsRatios of low- and high-fidelity training samples to degrees of freedom of nLF/nDOFs = 50 and nHF/nDOFs = 12.5 provided a surrogate model with a root mean squared error less than 5% and a similar convergence to the optimal design space when compared with the equivalent CFD-in-the-loop optimisation. Similar nacelle geometries and aerodynamic flow topologies were obtained for down-selected designs with a reduction of 92% in the computational cost. This highlights the potential benefits of this multi-fidelity approach for aerodynamic optimisation within a preliminary design stage.Originality/valueThe application of a multi-fidelity technique based on ANN to the aerodynamic shape optimisation problem of isolated nacelles is the key novelty of this work. The multi-fidelity aspect of the method advances current practices based on single-fidelity surrogate models and offers further reductions in computational cost to meet industrial design timescales. Additionally, guidelines in terms of low- and high-fidelity sample sizes relative to the number of design variables have been established.

ABSTRACTThis work studies the (2 + 1)-dimensional nonlinear Schrödinger equation which arises in optical fibre. Grey and black optical solitons of the model are reported using a suitable complex envelope ansatz solution. The integration lead to some certain conditions which must be satisfied for the solitons to exist. On applying the Chupin Liu's theorem to the grey and black optical solitons, we construct new sets of combined optical soliton solutions of the model. Moreover, classification of conservation laws (Cls) of the model is implemented using the multipliers approach. This is achieved by constructing a set of first-order multipliers of a system of nonlinear partial differential equations acquired by transforming the model into real and imaginary components are derived, which are subsequently used to construct the Cls.