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This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based design optimization (RBDO) subject to mixed design variables comprising both distributional and structural design variables.

The method involves a new augmented PDD of a high-dimensional stochastic response for statistical moments and reliability analyses; an integration of the augmented PDD, score functions, and finite-difference approximation for calculating the sensitivities of the first two moments and the failure probability with respect to distributional and structural design variables; and standard gradient-based optimization algorithms.

New closed-form formulae are presented for the design sensitivities of moments that are simultaneously determined along with the moments. A finite-difference approximation integrated with the embedded Monte Carlo simulation of the augmented PDD is put forward for design sensitivities of the failure probability.

In conjunction with the multi-point, single-step design process, the new method provides an efficient means to solve a general stochastic design problem entailing mixed design variables with a large design space. Numerical results, including a three-hole bracket design, indicate that the proposed methods provide accurate and computationally efficient sensitivity estimates and optimal solutions for RDO and RBDO problems.

THE importance of achieving a low structural weight is illustrated by simple estimates of the large decreases in aircraft gross weight and size made possible by conscientious weight saving in structural design. A brief review is then made of the many variables in aircraft design which affect the weight of the structure. The review is made chiefly to emphasize the close interplay in project work between the structural and aerodynamic effects of changes of layout. Finally some remarks are made about comparative structural design efficiency. It is concluded that good weight prediction formulae are at present the best means by which the structural design efficiencies of different aircraft may be readily compared.

This paper deals with structural shape and thickness optimization of axisymmetric shell structures loaded symmetrically. In the finite element stress analysis use is made of newly developed linear, quadratic, and cubic, variable thickness, C(0) elements based on axisymmetric Mindlin‐Reissner shell theory. An integrated approach is used to carry out the whole shape optimization process in a fully automatic manner. A robust, versatile and flexible mesh generator is incorporated with facilities for generating either uniform or graded meshes, with constant, linear, or cubic variation of thickness, pressure etc. The midsurface geometry and thickness variations of the axisymmetric shell structure are defined using cubic splines passing through certain key points. The design variables are chosen as the coordinates and/or the thickness at the key points. Variable linking procedures are also included. Sensitivity analysis is carried out using either a semi‐analytical method or a global finite difference method. The objective of the optimization is the weight minimization of the structure. Several examples are presented illustrating optimal shapes and thickness distributions for various shells. The changes in the bending, membrane and shear strain energies during the optimization process are also monitored.

The purpose of this paper is to re-examine the extant research on last-mile logistics (LML) models and consider LML’s diverse roots in city logistics, home delivery and business-to-consumer distribution, and more recent developments within the e-commerce digital supply chain context. The review offers a structured approach to what is currently a disparate and fractured field in logistics.

The systematic literature review examines the interface between e-commerce and LML. Following a protocol-driven methodology, combined with a “snowballing” technique, a total of 47 articles form the basis of the review.

The literature analysis conceptualises the relationship between a broad set of contingency variables and operational characteristics of LML configuration (push-centric, pull-centric, and hybrid system) via a set of structural variables, which are captured in the form of a design framework. The authors propose four future research areas reflecting likely digital supply chain evolutions.

To circumvent subjective selection of articles for inclusion, all papers were assessed independently by two researchers and counterchecked with two independent logistics experts. Resulting classifications inform the development of future LML models.

The design framework of this study provides practitioners insights on key contingency and structural variables and their interrelationships, as well as viable configuration options within given boundary conditions. The reformulated knowledge allows these prescriptive models to inform practitioners in their design of last-mile distribution.

Improved LML performance would have positive societal impacts in terms of service and resource efficiency.

This paper provides the first comprehensive review on LML models in the modern e-commerce context. It synthesises knowledge of LML models and provides insights on current trends and future research directions.

The purpose of this paper is to analyse how changes in a set of structural design variables (i.e. liaison position, networked design, innovation teams and work teams) affect the creation of new knowledge within organizations. The enablers intention, autonomy, fluctuation and creative chaos, redundancy, variety, and trust and commitment, taken from Nonaka's framework, are used as intermediate variables.

A sample of 167 large Spanish companies was used to empirically test a general relational model.

The analysis yielded two main conclusions. First, the relationship between structural variables and enablers, and, second, the relationship of enablers with knowledge creation emerged as highly relevant for knowledge creation in organizations.

A major limitation of this study was the relatively small number of variables used to define organizational structure. In reality, a large number of variables combine to create organizational structure, yet this study only included four: liaison position, networked design, innovation teams and work teams. A further limitation is the importance of the organizational context itself, which was not addressed in this study.

This research has yielded findings that can help firms to understand and appreciate the changes that may occur in certain organizational design variables that affect knowledge creation. Equally, this research shows that knowledge creation has the potential to act as a catalyst for innovation, and may consequently drive change within the firm.

Despite a long tradition of research into organizations and the ways in which these entities create knowledge, the literature requires enhancing through the publication of articles that provide a deeper knowledge of the context and tools that aid knowledge creation. The novel approach adopted in the current study verified whether certain variables related to organization design (i.e. liaison positions, networked design, innovation teams and work teams) exert a relevant influence on knowledge creation.

This paper describes an integrated structural optimization procedure in the vehicle structural concept design using multilevel decomposition technique. The structural responses in the lower level are represented in terms of local quantities that are the intermediate parameters or the detailed dimensions based on the parametric distributed screen from design and manufacturing constraints. And this technique is applied to develop the aluminum vehicle structure at concept design. We have the very efficiency results that decide the characteristics of master section and joint stiffness of vehicle structure. In the comparison with the base model the bending stiffness and torsional stiffness of the developed aluminum vehicle structure increase around 45% and 35% respectively, and the weight reduction is around 30%.

This paper deals with structural shape optimization of vibrating prismatic shells and folded plates. The finite strip method is used to determine the natural frequencies and modal shapes based on Mindlin‐Reissner shell theory which allows for transverse shear deformation and rotatory inertia effects. An automated optimization procedure is adopted which integrates finite strip analysis, parametric cubic spline geometry definition, automatic mesh generation, sensitivity analysis and mathematical programming methods. The objective is to maximize the fundamental frequency by changing thickness and shape design variables defining the cross‐section of the structure, with a constraint that the total volume of the structure remains constant. A series of examples is presented to highlight various features of the optimization procedure as well as the accuracy and efficiency of finite strip method.

The aim of this paper is to present a novel multifactor structural optimisation method incorporating reliability performance.

This research addresses structural optimisation problems in which the design is required to satisfy multiple performance criteria, such as strength, stiffness, mass and reliability under multiple loading cases simultaneously. A MOST technique is extended to accommodate the reliability‐related optimisation. Structural responses and geometrical sensitivities are analysed by a FE method, and reliability performance is calculated by a reliability loading‐case index (RLI). The evaluation indices of performances and loading cases are formulated, and an overall performance index is presented to quantitatively evaluate a design.

The proposed method is applicable to multi‐objective, multi‐loading‐case, multi‐disciplinary and reliability‐related optimisation problems. The applications to a star‐like truss structure and a raised‐access floor panel structure confirmed that the method is highly effective and efficient in terms of structural optimisation.

A systematic method is proposed. The optimisation method combines the MOST technique with a RLI (a new alternative route to calculate the reliability index at multiple loading cases) using a parametric FE model.

On-orbit assembly technology is a promising research topic in spaceflight field. For purposes of studying the dynamic performance and reducing weight of an on-orbit assembly satellite structure frame, this paper aims to propose a structural optimization design method based on natural frequency.

The dynamic stability of the satellite under working condition depends on the mechanical properties of the structure matrix. A global structural optimization model is established, with the objective of mass minimization and the constraints of given natural frequencies and given structure requirements. The structural optimization and improvement design method is proposed using sequential quadratic programming calculation.

The optimal result of objective function is effectively obtained, and the best combination of structural geometric parameters is configurated. By analyzing the relationship between the structural variables and optimization parameters, the primary and secondary factors to the mass optimization process of the microsatellite satisfying the dynamic performance requirements are obtained, which improves the effectiveness and accuracy of the system optimization design.

This method can coordinate the relation between satellite vibration stability and weight reduction, which provides an effective way for the optimization design of on-orbit assembly microsatellite. It has reference significance for the similar spacecraft framework structure design.

In modeling an aircraft wing, structural idealizations are often employed in hand calculations to simplify the structural analysis. In real applications of structural design, analysis and optimization, finite element methods are used because of the complexity of the geometry, combined and complex loading conditions. The purpose of this paper is to give a comprehensive study on the effect of using different structural idealizations on the design, analysis and optimization of thin walled semi-monocoque wing structures in the preliminary design phase.

In the design part of the paper, wing structures are designed by employing two different structural idealizations that are typically used in the preliminary design phase. In the structural analysis part, finite element analysis of one of the designed wing configurations is performed using six different one and two dimensional finite element pairs which are typically used to model the sub-elements of semi-monocoque wing structures. Finally in the optimization part, wing structure is optimized for minimum weight by using finite element models which have the same six different finite element pairs used in the analysis phase.

Based on the results presented in the paper, it is concluded that with the simplified methods, preliminary sizing of the wing configurations can be performed with enough confidence as long as the simplified method based designs are also optimized iteratively, which is what is practiced in the design phase of this study.

This research aims at investigating the effect of using different one and two dimensional element pairs on the final analyzed and optimized configurations of the wing structure, and conclusions are inferred with regard to the sensitivity of the optimized wing configurations with respect to the choice of different element types in the finite element model.