Use of structural dynamic and fatigue sensitivity derivatives in an automotive design optimization

Direct accounting for durability rarely finds its way into multidisciplinary optimization. Though reduction of loads by some means can certainly have a beneficial influence on the fatigue performance of a structure, changes in load levels are not a direct measure of the influence of design changes on fatigue performance. In this paper, a previously described method for calculating design sensitivities of a fatigue performance index is used in a simple optimization of suspension damping and stiffness on a simple truck model. The dynamic loading is a conceptual representation of the industrial practice of road testing and simulation. Results demonstrate the feasibility of using a direct measure of fatigue performance in formal structural optimization.     

A sequential approximate programming strategy for reliability-based structural optimization

Although reliability-based structural optimization (RBSO) is recognized as a rational structural design philosophy that is more advantageous to deterministic optimization, most common RBSO is based on straightforward two-level approach connecting algorithms of reliability calculation and that of design optimization. This is achieved usually with an outer loop for optimization of design variables and an inner loop for reliability analysis. A number of algorithms have been proposed to reduce the computational cost of such optimizations, such as performance measure approach, semi-infinite programming, and mono-level approach. Herein the sequential approximate programming approach, which is well known in structural optimization, is extended as an efficient methodology to solve RBSO problems. In this approach, the optimum design is obtained by solving a sequence of sub-programming problems that usually consist of an approximate objective function subjected to a set of approximate constraint functions. In each sub-programming, rather than direct Taylor expansion of reliability constraints, a new formulation is introduced for approximate reliability constraints at the current design point and its linearization. The approximate reliability index and its sensitivity are obtained from a recurrence formula based on the optimality conditions for the most probable failure point (MPP). It is shown that the approximate MPP, a key component of RBSO problems, is concurrently improved during each sub-programming solution step. Through analytical models and comparative studies over complex examples, it is illustrated that our approach is efficient and that a linearized reliability index is a good approximation of the accurate reliability index. These unique features and the concurrent convergence of design optimization and reliability calculation are demonstrated with several numerical examples.     

Comparison of two different approaches for making design sensitivity analysis an integrated part of finite element analysis

This paper presents a comparison of two approaches for incorporating design sensitivity calculations into finite element analysis. The formulations depend on the implicit differentiation method and require few additional calculations to obtain the design sensitivity derivatives. The first approach by-passes the direct calculation of the stiffness matrix derivatives by calculating the sensitivity derivatives at the stress recovery stage of the analysis. The second approach depends on the direct calculation of the derivatives of the stiffness matrix, which are stored for re-use in multiple load case analyses, and subsequent matrix multiplications to evaluate the design sensitivities. The two approaches are developed and implemented to calculate the design sensitivities for continuum and structural isoparametric elements. In addition, a criterion is developed to aid in deciding which approach is better for a given number of load cases. To demonstrate the validity of the developed criterion and to evaluate the relative merits of each approach, some sensitivity calculation test problems are solved with different numbers of load cases.     

Efficient design sensitivity derivatives for multi-load case structures as an integrated part of finite element analysis

In most structural optimization problems the accurate calculation of design sensitivity derivatives is required many times during the optimization process. For large structures with multi-load cases the computational costs are sometimes prohibitive. In this paper an approach for incorporating design sensitivity calculations into the finite element analysis of multi-load case structures is presented. A formulation designed to minimize the computational time for the assembled stiffness matrix derivatives is discussed for different element types. The formulation depends on the implicit differentiation method and requires few additional calculations to obtain the design sensitivity derivatives. The approach is developed and implemented to calculate the design sensitivities for continuum and structural isoparametric elements. To demonstrate the accuracy and efficiency of the developed approach some test cases using different structural and continuum element types are presented.     

Optimal design of machine components using notch correction and plasticity models

Shape optimization computational technology is used in order to maximize life time of notched machine/structural components in low cycle fatigue regime. The present approach is composed of three steps: (i) stress–strain calculation using notch correction and plasticity models, (ii) estimation of critical plane to asses fatigue lives, (iii) formulation of the optimization problem with constraint set on the number of cycles corresponding to crack initiation. The optimal design procedure is a combination of the computer aided geometrical design mathematical methods for the shape definition, the boundary element method used for analysis of the response quantities, assisted by the sequential linear programming method with move limits. Numerical examples display significant increase in the number of cycles corresponding to crack initiation phase in comparison to traditional (regular) notch shapes.     

Reliability-based shape optimization of structures undergoing fluid–structure interaction phenomena

Fluid–structure interaction phenomena are often roughly approximated when the stochastic nature of a system is considered in the design optimization process, leading to potentially significant epistemic uncertainty. In this paper, after reviewing the state-of-the-art methods in robust and reliability-based design optimization of problems undergoing fluid–structure interaction phenomena, a computational framework is presented that integrates a high-fidelity aeroelastic model into reliability-based design optimization. The design optimization problem is formulated pursuant to the reliability index and performance measure approaches. The system reliability is evaluated by a first-order reliability analysis method. The steady-state aeroelastic problem is described by a three-field formulation and solved by a staggered procedure, coupling a potentially detailed structural finite element model and a finite volume discretization of the Euler flow. The design and imperfection sensitivities are computed by evaluating the analytically derived direct and adjoint coupled aeroelastic sensitivity equations. The computational framework is verified by the optimization of three-dimensional wing structures. The lift-to-drag ratio is maximized, subject to stress constraints, by varying shape, thickness, and material properties. Uncertainties in structural parameters, including design parameters, operating conditions, and modeling uncertainties are considered. The results demonstrate the need for reliability-based optimization methods, for the design of structures undergoing fluid–structure interaction phenomena, and the applicability of the proposed framework to realistic design problems. Comparing the optimization results for different levels of uncertainty shows the importance of accounting for uncertainties in a quantitative manner.     

Simultaneous parameter and tolerance optimization of structures via probability-interval mixed reliability model

Both structural sizes and dimensional tolerances strongly influence the manufacturing cost and the functional performance of a practical product. This paper presents an optimization method to simultaneously find the optimal combination of structural sizes and dimensional tolerances. Based on a probability-interval mixed reliability model, the imprecision of design parameters is modeled as interval uncertainties fluctuating within allowable tolerance bounds. The optimization model is defined as to minimize the total manufacturing cost under mixed reliability index constraints, which are further transformed into their equivalent formulations by using the performance measure approach. The optimization problem is then solved with the sequential approximate programming. Meanwhile, a numerically stable algorithm based on the trust region method is proposed to efficiently update the target performance points (TPPs) and the worst case points (WCPs), which shows better performance than traditional approaches for highly nonlinear problems. Numerical results reveal that reasonable dimensions and tolerances can be suggested for the minimum manufacturing cost and a desirable structural safety.     

Inverse analysis method using MPP-based dimension reduction for reliability-based design optimization of nonlinear and multi-dimensional systems

There are two commonly used analytical reliability analysis methods: linear approximation - first-order reliability method (FORM), and quadratic approximation - second-order reliability method (SORM), of the performance function. The reliability analysis using FORM could be acceptable in accuracy for mildly nonlinear performance functions, whereas the reliability analysis using SORM may be necessary for accuracy of nonlinear and multi-dimensional performance functions. Even though the reliability analysis using SORM may be accurate, it is not as much used for probability of failure calculation since SORM requires the second-order sensitivities. Moreover, the SORM-based inverse reliability analysis is rather difficult to develop.This paper proposes an inverse reliability analysis method that can be used to obtain accurate probability of failure calculation without requiring the second-order sensitivities for reliability-based design optimization (RBDO) of nonlinear and multi-dimensional systems. For the inverse reliability analysis, the most probable point (MPP)-based dimension reduction method (DRM) is developed. Since the FORM-based reliability index (β) is inaccurate for the MPP search of the nonlinear performance function, a three-step computational procedure is proposed to improve accuracy of the inverse reliability analysis: probability of failure calculation using constraint shift, reliability index update, and MPP update. Using the three steps, a new DRM-based MPP is obtained, which estimates the probability of failure of the performance function more accurately than FORM and more efficiently than SORM. The DRM-based MPP is then used for the next design iteration of RBDO to obtain an accurate optimum design even for nonlinear and/or multi-dimensional system. Since the DRM-based RBDO requires more function evaluations, the enriched performance measure approach (PMA+) with new tolerances for constraint activeness and reduced rotation matrix is used to reduce the number of function evaluations.     

Full analytical sensitivities in NURBS based isogeometric shape optimization

Non-uniform rational B-spline (NURBS) has been widely used as an effective shape parameterization technique for structural optimization due to its compact and powerful shape representation capability and its popularity among CAD systems. The advent of NURBS based isogeometric analysis has made it even more advantageous to use NURBS in shape optimization since it can potentially avoid the inaccuracy and labor-tediousness in geometric model conversion from the design model to the analysis model.Although both positions and weights of NURBS control points affect the shape, until very recently, usually only control point positions are used as design variables in shape optimization, thus restricting the design space and limiting the shape representation flexibility.This paper presents an approach for analytically computing the full sensitivities of both the positions and weights of NURBS control points in structural shape optimization. Such analytical formulation allows accurate calculation of sensitivity and has been successfully used in gradient-based shape optimization.The analytical sensitivity for both positions and weights of NURBS control points is especially beneficial for recovering optimal shapes that are conical e.g. ellipses and circles in 2D, cylinders, ellipsoids and spheres in 3D that are otherwise not possible without the weights as design variables.     

Optimal design of aircraft structures with damage tolerance requirements

Damage tolerance analysis (DTA) was considered in the global design optimization of an aircraft wing structure. Residual strength and fatigue life requirements, based on the damage tolerance philosophy, were investigated as new design constraints. The global/local finite element approach allowed local fatigue requirements to be considered in the global design optimization. AFGROW fatigue crack growth analysis provided a new strength criterion for satisfying damage tolerance requirements within a global optimization environment. Initial research with the ASTROS program used this damage tolerance constraint to optimize cracked skin panels on the lower wing of a fighter/attack aircraft. For an aerodynamic and structural model of this type of aircraft, ASTROS simulated symmetric and asymmetric maneuvers during the optimization. Symmetric maneuvers, without underwing stores, produced the highest stresses and drove the optimization of the inboard lower wing skin. Asymmetric maneuvers, with underwing stores, affected the optimum thickness of the outboard hard points. Subsequent design optimizations included DTA and von Mises stress constraints simultaneously. In the configuration with no stores, the optimization was driven by the DTA constraint and, therefore, DTA requirements can have an active role to play in preliminary aircraft design.     

Adjoint network method applied to the performance sensitivities of microwave amplifiers

This work focuses on the performance sensitivities of microwave amplifiers using the “adjoint network and adjoint variable” method, via “wave” approaches, which includes sensitivities of the transducer power gain, noise figure, and magnitudes and phases of the input and output reflection coefficients. The method can be extended to sensitivities of the other performance measure functions. The adjoint‐variable methods for design‐sensitivity analysis offer computational speed and accuracy. They can be used for efficiency‐based gradient optimization, in tolerance and yield analyses. In this work, an arbitrarily configured microwave amplifier is considered: firstly, each element in the network is modeled by the scattering matrix formulation, then the topology of the network is taken into account using the connection scattering‐matrix formulation. The wave approach is utilized in the evaluation of all the performance‐measurement functions, then sensitivity invariants are formulated using Tellegen's theorem. Performance sensitivities of the T‐ and Π‐types of distributed‐parameter amplifiers are considered as a worked example. The numerical results of T‐ and Π‐type amplifiers for the design targets of noise figure F_req = 0.46 dB ? 1,12 and V_ireq = 1, G_Treq = 12 dB ? 15.86 in the frequency range 2–11 GHz are given in comparison to each other. Furthermore, analytical methods of the “gain factorisation” and “chain sensitivity parameter” are applied to the gain and noise sensitivities as well. In addition, “numerical perturbation” is applied to calculation of all the sensitivities. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006.     

Topological optimization of continuum structures with design-dependent surface loading – Part I: new computational approach for 2D problems

This paper describes a new computational approach for optimum topology design of 2D continuum structures subjected to design-dependent loading. Both the locations and directions of the loads may change as the structural topology changes. A robust algorithm based on a modified isoline technique is presented that generates the appropriate loading surface which remains on the boundary of potential structural domains during the topology evolution. Issues in connection with tracing the variable loading surface are discussed and treated in the paper. Our study indicates that the influence of the variation of element material density is confined within a small neighbourhood of the element. With this fact in mind, the cost of the calculation of the sensitivities of loads may be reduced remarkably. Minimum compliance is considered as the design problem. There are several models available for such designs. In the present paper, a simple formulation with weighted unit cost constraints based on the expression of potential energy is employed. Compared to the traditional models (i.e., the SIMP model), it provides an alternative way to implement the topology design of continuum structures. Some 2D examples are tested to show the differences between the designs obtained for fixed, design-independent loading, and for variable, design-dependent loading. The general and special features of the optimization with design-dependent loads are shown in the paper, and the validity of the algorithm is verified. An algorithm dealing with 3D design problems is described in Part II, which is developed from the 2D algorithm in the present Part I of the paper.     

Special purpose symbolic computation software with application to the optimization of composite laminates

Symbolic computation software is developed in the C language for the transformation of coordinate axes, failure analysis and the calculation of design sensitivities. These computations arise in the design optimization studies of structures made of fibre composite materials. The symbolic computations are integrated into an optimization algorithm resulting in a combined symbolic and numerical approach to determine the optimal design. The results are illustrated by considering the minimum thickness design of a laminate under in-plane loads. For this problem, the special purpose symbolic computation software handles matrices whose entries are series of double trigonometric functions, and determines the component functions of the design objective.     

基于模态瞬态法的发动机罩焊点疲劳优化

针对某车型整车耐久路试过程中发动机罩铰链加强板焊点出现开裂的问题,采用模态瞬态法对发动机罩焊点进行疲劳分析。根据发动机罩模态应变能分布情况优化铰链加强板结构和焊点分布,试验车整改后在整车耐久路试中发动机罩焊点未再出现开裂现象。发动机罩铰链加强板焊点开裂是振动疲劳问题,采用基于惯性释放的准静态法计算疲劳损伤不能预测焊点开裂问题,采用模态瞬态法疲劳计算方法才能更好地预测发动机罩焊点疲劳损伤。从模态应变能角度对结构振动疲劳开裂问题进行优化能明显提高优化效率。     

Optimal cross-section and configuration design of elastic-plastic structures subject to dynamic cyclic loading

This paper shows an optimal design problem with continuum variational formulation, applied to nonlinear elasticplastic structures subject to dynamic loading. The total Lagrangian procedure is used to describe the response of the structure. The direct differentiation method is used to obtain the sensitivities of the structural response that are needed to solve the optimization problem. Since unloading and reloading of the structure are allowed, the structural response is path-dependent and an additional step is needed to integrate the constitutive equations. It can be shown, consequently, that design sensitivity analysis is also path-dependent. A finite element method with implicit time integration is used to discretize the state and sensitivity equations.A mathematical programming approach is used for the optimization process. Numerical applications are performed on a 3-D truss structure, where cross-sectional areas and nodal point coordinates are treated as design variables. Optimal designs have been obtained and compared by using two different strategies: a twolevel strategy where the levels are defined according to the type of design variables, cross sectional areas or node coordinates, and optimizing simultaneously with respect to both types of design variables. Comparisons have also been made between optimal designs obtained by considering or not considering the inertial term of the structural equilibrium.     

Accuracy test of sensitivity analysis in the semi-analytic method with respect to configuration variables

Configuration optimization is a structural optimization method where the geometrical shape of the structures can be changed during the optimization process. Sensitivity informations are required in the general optimization and quite costly. Especially, they are extemely expensive in the structural optimization where the finite element analysis is utilized. Since the nodal coordinates are regarded as design variables in the configuration optimization, the sensitivities according to the nodal coordinates must be calculated. The characteristics of the configuration optimization is that the transformation matrix in the finite element analysis is a function of design variables. Thus the sensitivity calculation in the configuration optimization is even more complicated. For the efficient sensitivity calculations, various methods have been proposed. They are the analytic method (AM), overall finite difference method (OFD), and semi-analytic method (SM). The semi-analytic method consists of the forward and central difference approximation. This study has been conducted to choose an appropriate method by comparison based on the mathematical and numerical aspects. Some standard structural problems are selected for the evaluations.     

Shape optimal design of an engine exhaust manifold

An engine exhaust manifold made of cast iron cracks during thermal shock testing. The test process is simulated by finite element analysis. The manifold is formulated as a linear heat transfer and thermoelasticity problem in a variational form. Analytical expressions for shape design sensitivities of general three-dimensional problems are presented, using the material derivative approach. A hybrid approach is described and used during the optimization process. This approach takes advantage of the direct and the adjoint variable methods and is the most efficient in calculating the sensitivity of the structural responses. After the finite element model is verified by comparing the results with those from testing, the engine exhaust manifold is optimized with respect to its geometry.     

Robust design of non-linear structures using optimization methods

The robust design of non-linear structures with path-dependent response is stated as a two-criteria optimization problem and is solved by the method of mathematical programming. To this end, the perturbation technique is applied in conjunction with the incremental loading procedure for the response moment analysis of path-dependent non-linear structural systems with random parameters. Furthermore, the sensitivities of mean and variance of the structural performance function are evaluated using direct differentiation in the framework of perturbation based stochastic finite element analysis. By introducing a weighting factor in the compound objective––resp. desirability function, and feasibility indices in the constraints, the mathematical model of structural robust design problem is formulated and is solved with a gradient-based algorithm. Numerical examples demonstrate the applicability of the presented method.