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Optimization of structural systems under reliability‐based performance constraints is an important problem at present receiving too little attention. This problem is investigated in this paper. In developing the reliability‐based optimization approach to the design of framed structures, we review first the general formulation of the deterministic optimization problem and present some of the main features of two general‐purpose deterministic optimization programs. A computer‐automated reliability‐based optimum design procedure is then presented by which the concept of reliability analysis with regard to both serviceability and ultimate performance constraints is combined with that of the minimum weight design to achieve an optimum trade‐off between the global reliability and the total cost. The procedure is feasible for application in system optimization of both steel and reinforced concrete structures.

This paper describes an automated design system for nuclear structural components under complicated loading conditions. As a basic strategy of designing structures considering various loading conditions, the “generate and test” strategy is adopted because of simplicity and broad applicability. The object‐oriented knowledge representation technique is adopted to store knowledge modules related to design problems, while the data‐flow processing technique is utilized as an inference mechanism among the knowledge modules. As efficient design modification mechanisms, the present system utilizes two approaches, (a) an empirical approach based on experts’ empirical knowledge and the fuzzy control, and (b) a mathematical approach based on numerical sensitivity analysis. Using the present system, one can also obtain a “design window” which designates a satisfaction area for all design criteria in a design variable space. The fundamental performances of this system are clearly demonstrated through the design of a two‐dimensional model of the fusion first wall with a circular cooling channel.

This paper aims to clarify the relationship between mechanical behaviors and the underlying geometry of periodic cellular structures. Particularly, the answer to the following research question is investigated: Can seemingly different geometries of the repeating unit cells of periodic cellular structure result in similar functional behaviors? The study aims to cluster the geometry-functional behavior relationship into different categories.

Specifically, the effects of the geometry on the compressive deformation (mechanical behavior) responses of multiple standardized cubic periodic cellular structures (CPCS) at macro scales are investigated through both physical tests and finite element simulations of three-dimensional (3D) printed samples. Additionally, these multiple CPCS can be further nested into the shell of 3D models of various mechanical domain parts to demonstrate the influence of their geometries in practical applications.

The paper provides insights into how different CPCS (geometrically different unit cells) influence their compressive deformation behaviors. It suggests a standardized strategy for comparing mechanical behaviors of different CPCS.

This paper is the first work in the research domain to investigate if seemingly different geometries of the underlying unit cell can result in similar mechanical behaviors. It also fulfills the need to infill and lattify real functional parts with geometrically complex unit cells. Existing work mainly focused on simple shapes such as basic trusses or cubes with spherical holes.

This paper demonstrates the use of genetic algorithms (GAs) for size optimization of trusses. The concept of rebirthing is shown to be considerably effective for problems involving continuous design variables. Some benchmark examples are studied involving 4‐bar, 10‐bar, 64‐bar, 200‐bar and 940‐bar two‐dimensional trusses. Both continuous and discrete variables are considered.

Computer programs which model the static, dynamic and aeroelastic response of wing structures, and which permit optimisation of such structures, have been under development for more than 30 years. However, the industrial application of these programs remains small. This paper provides an overview of some of the existing optimisation methods which may be applied at various stages during the design of wing structures. An indication of the variety of design variables, constraints and objective functions available within these methods is given. Some general conclusions are drawn, about both the limitations and potential application of such structural optimisation techniques.

The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and genetic hybrid algorithm (PGSA-GA), for solving structural optimization problems.

PGSA-GA is based on PGSA and three improved strategies, namely, elitist strategy of morphactin concentration calculation, strategy of intelligent variable step size and strategy of initial growth point selection based on GA. After a detailed formulation and explanation of its implementation, PGSA-GA is verified using the examples of typical truss and single-layer lattice shell.

Improved PGSA-GA was implemented and optimization was carried out for two typical optimization problems; then, a comparison was made between the PGSA-GA and other methods. The results show that the method proposed in the paper has the advantages of high efficiency and rapid convergence, which enable it to be used for the optimization of various types of steel structures.

Through the examples of typical truss and single-layer lattice shell, it shows that the optimization efficiency and effect of PGSA-GA are better than those of other algorithms and methods, such as GA, secondary optimization method, etc. The results show that PGSA-GA is quite suitable for structural optimization.

The computational drawbacks of existing numerical methods have forced researchers to rely on heuristic algorithms. Heuristic methods are powerful in obtaining the solution of optimization problems. Although they are approximate methods (i.e. their solution are good, but not provably optimal), they do not require the derivatives of the objective function and constraints. Also, they use probabilistic transition rules instead of deterministic rules. The purpose of this paper is to present an improved ant colony optimization (IACO) for constrained engineering design problems.

IACO has the capacity to handle continuous and discrete problems by using sub‐optimization mechanism (SOM). SOM is based on the principles of finite element method working as a search‐space updating technique. Also, SOM can reduce the size of pheromone matrices, decision vectors and the number of evaluations. Though IACO decreases pheromone updating operations as well as optimization time, the probability of finding an optimum solution is not reduced.

Utilizing SOM in the ACO algorithm causes a decrease in the size of the pheromone vectors, size of the decision vector, size of the search space, the number of function evaluations, and finally the required optimization time. SOM performs as a search‐space‐updating rule, and it can exchange discrete‐continuous search domain to each other.

The suitability of using ACO for constrained engineering design problems is presented, and applied to optimal design of different engineering problems.

The purpose of this paper is to present a structural design and optimization module for aircraft structures that can be used stand-alone or in a high-fidelity multidisciplinary design optimization (MDO) process. The module is capable of dealing with different design concepts and novel materials properly. The functionality of the module is also demonstrated.

For fast sizing and optimization, linear static finite element (FE) models are used to obtain inner loads of the structural components. The inner loads and the geometry are passed to a software, where a comprehensive set of analytical failure criteria is applied for the design of the structure. In addition to conventional design processes, the objects of stiffened panels like skin and stringer are not optimized separately and discrete layups can be considered for composites. The module is connected to a design environment, where an automated steering of the overall process and the generation of the FE models is implemented.

The exemplary application on a transport aircraft wing shows the functionality of the developed module.

The weight benefit of not optimizing skin and stringer separately was shown. Furthermore, with the applied approach, a fast investigation of different aircraft configurations is possible without constraining too many design variables as it often occurs in other optimization processes. The flexibility of the module allows numerous investigations on influence of design concepts and failure criteria on the mass and layout of aircraft wings.

Testing is one of the indispensable activities in software development and is being adopted as an independent course by software engineering (SE) departments at universities worldwide. The purpose of this paper is to carry out an investigation of the performance of learners about testing, given the tendencies in the industry and motivation caused by the unavailability of similar studies in software testing field.

This study is based on the data collected over three years (between 2012 and 2014) from students taking the software testing course. The course is included in the second year of undergraduate curriculum for the bachelor of engineering (SE).

It has been observed that, from the performance perspective, automated testing outperforms structural and functional testing techniques, and that a strong correlation exists among these three approaches. Moreover, a strong programming background does help toward further success in structural and automated testing, but has no effect on functional testing. The results of different teaching styles within the course are also presented together with an analysis exploring the relationship between students’ gender and success in the software testing course, revealing that there is no difference in terms of performance between male and female students in the course. Moreover, it is advisable to introduce teaching concepts one at a time because students find it difficult to grasp the ideas otherwise.

These findings are based on the analysis conducted using three years of data collected while teaching a course in testing. Obviously, there are some limitations to this study. For example, student’s strength in programming is calculated using the score of C programming courses taken in previous year/semester. Such scores may not reflect their current level of programming knowledge. Furthermore, attempt was made to ensure that the exercises given for different testing techniques have similar difficulty level to guarantee that the difference in success between these testing techniques is due to the inherent complexity of the technique itself and not because of different exercises. Still, there is small probability that a certain degree of change in success may be due to the difference in the difficulty levels of the exercises. As such, it is obviously premature to consider the present results as final since there is a lack of similar type of studies, with which the authors can compare the results. Therefore, more work needs to be done in different settings to draw sound conclusions in this respect.

Although there are few studies (see e.g. Chan et al., 2005; Garousi and Zhi, 2013; Ng et al., 2004) exploring the preference of testers over distinct software testing techniques in the industry, there appears to be no paper comparing the preferences and performances of learners in terms of different testing techniques.

To obtain a good start configuration in the early design phase, simulation tools are used to create a large number of product designs and to evaluate their performance. To reduce the effort for the model generation, analysis and evaluation, a design environment for thin-walled lightweight structures (DELiS) with the focus on structural mechanics of aircrafts has been developed.

The core of DELiS is a parametric model generator, which creates models of thin-walled lightweight structures for the aircraft preliminary design process. It is based on the common parametric aircraft configuration schema (CPACS), which is an abstract aircraft namespace. DELiS facilitates interfaces to several commercial and non-commercial finite element solvers and sizing tools.

The key principles and the advantages of the DELiS process are illustrated. Also, a convergence study of the finite element model of the wing and the fuselage and the result on the mass after the sizing process are shown. Due to the high flexibility of model generation with different levels of detail and the interface to the exchange database CPACS, DELiS is well suited to study the structural behaviour of different aircraft configurations in a multi-disciplinary design process.

The abstract definition of the object-oriented model allows several dimensions of variability, such as different fidelity levels, for the resulting structural model. Wings and fuselages can be interpreted as finite beam models, to calculate the global dynamic behaviour of a structure, or as finite shell models.