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Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

Considering the randomness of physical parameters of structural material, dynamic characteristic topology optimization mathematical model based on reliability of planar continuum structures is built in this paper. In which topology information variables of the structure are taken as design variables, minimizing the mean value of total structural weight as objective function and satisfying the reliability requirement of structural dynamic characteristic as constraints. In the process of optimization, the ESO method based on probability is adopted as solution strategy. At the same time, distribution function method is utilized to convert the reliability constraints into conventional constraints formally. A square thin plate with four sides fixed is used as an example to demonstrate the rationality and validity of the presented model.

The structural optimization presented in this paper is based on an evolutionary procedure, developed recently, in which the low stressed part of a structure is removed from the structure step‐by‐step until an optimal design is obtained. Various tests have shown the effectiveness of this evolutionary procedure. The purpose of this paper is to present applications of such an evolutionary procedure to the optimal design of structures with multiple load cases or with a traffic (moving) load.

Based on the asymptotic solution for predicted natural frequencies of a two‐dimensional elastodynamic problem from the finite element analysis, presents the concept of the asymptotic error, which is an approximate error but tends to the exact error when the characteristic length of elements approaches zero, and a practical error estimator. The present practical error estimator contains two criteria: one is the error estimator criterion, the other the finite element mesh design criterion. Using this practical error estimator, not only can the accuracy of a finite element solution for natural frequencies of a two‐dimensional elastodynamic problem be directly evaluated without any further finite element calculation, but also a new target finite element mesh for the desired accuracy of solution can be immediately designed from the relevant information of an original finite element solution. Generally, for the purpose of designing a new target finite element mesh, this original finite element solution is obtainable from a very coarse mesh of a few elements and usually does not satisfy the accuracy requirement. Since the new target finite element mesh could result in a finite element solution with a desire accuracy, the finite element solution so obtained can be used for a structural design in engineering practice. The related numerical results from vibration problems of three representative plates of different shapes under plane stress conditions have demonstrated the correctness and applicability of the present practical error estimator.

Most engineering products contain more than one component or structural element, a consideration that needs to be appreciated during the design process and beyond, to manufacturing, transportation, storage and maintenance. The allocation and design of component interconnections (such as bolts, rivets, or springs, spot‐welds, adhesives, others) usually play a crucial role in the design of the entire multi‐component system. This paper extends the evolutionary structural optimization method to the generic design problems of connection topology. The proposed approach consists of a simple cycle of a finite element analysis followed by a rule‐driven element removal process. To make the interconnection elements carry as close to uniform a load as possible, a “fully stressed” design criterion is adopted. To determine the presence and absence of the interconnection elements, the usage efficiencies of fastener elements are estimated in terms of their relative stress levels. This avoids the use of gradient‐based optimization algorithms and allows designers to readily seek an optimization of connection topology, which can be implemented in their familiar CAD/CAE design platforms. To demonstrate the capabilities of the proposed procedure, a number of design examples are presented in this paper.

Describes development work to combine the basic ESO with the additive evolutionary structural optimisation (AESO) to produce bidirectional ESO whereby material can be added and can be removed. It will be shown that this provides the same results as the traditional ESO. This has two benefits, it validates the whole ESO concept and there is a significant time saving since the structure grows from a small initial one rather than contracting from a sometimes huge initial one where 90 per cent of the material gets removed over many hundreds of finite element analysis (FEA) evolutionary cycles. Presents a brief background to the current state of Structural Optimisation research. This is followed by a discussion of the strategies for the bidirectional ESO (BESO) algorithm and two examples are presented.

In continuation of the recent development of Evolutionary Structural Optimisation (ESO) applied to the simultaneous objective to maximise the natural frequency and to minimise the mean compliance, presents the Multicriteria ESO optimisation of two new criteria. This has been done with the use of four different multicriteria methods. Three examples have been used to verify the usefulness and capability of these methods applied to ESO in the context of the aforementioned criteria. Concluded that the ESO weighting method is proficient in presenting the designer with a range of options (of Pareto attribute) taking into account multiple criteria, and the global criterion method has the tendency to produce shapes and topologies that resemble that of the weighted 50 per cent: 50 per cent method. Likewise, the logical OR operator method produced designs that corresponded directly to those of 100 per cent stiffness weighted criteria. No clear resemblance could be concluded with the case of the logical AND operator method.

An automated fully stressed design approach based on the Xie and Steven algorithm is presented. With this algorithm a fully stressed design is obtained by a gradual removal of low stressed material. By applying this evolutionary procedure a layout or topology of a structure can be found from an initial block of material. A fully integrated, interactive program is presented which incorporates automatic mesh generation, finite element analysis and the fully stressed design algorithm. The feasibility of the approach is demonstrated using several examples.

Introduces a faster and improved structural optimisation method which combines fixed grid finite element analysis (FG FEA) and evolutionary structural optimisation (ESO). ESO optimises a structure by removing a few elements at every iteration. FG methods allow fast mesh generation, fast solution and fast re‐evaluation of the modified meshes. The implementation of FG into the ESO process eliminates the need for regenerating the mesh and a few arithmetic calculations replace the full regeneration of the stiffness matrix every time the structure is modified. This greatly reduces the solution time, and the examples presented in this paper demonstrate and validate the method.

This paper shows how the evolutionary structural optimization (ESO) algorithm can be used to achieve a multiple criterion design for a structure in a thermal environment. The proposed thermal ESO procedure couples an evolutionary iterative process of a finite element heat conduction solution and a finite element thermoelastic solution. The overall efficiency of material usage is measured in terms of the combination of thermal stress levels and heat flux densities by using a combination strategy with weighting factors. The ESO method then works by eliminating from the structural domain under‐utilized material. In this paper, a practical design example of a printed circuit board substrate is presented to illustrate the capabilities of the ESO algorithm for thermal design optimization in multiple load environments.