Improved structure optimization for fuzzy-neural networks

Fuzzy-neural-network-based inference systems are well-known universal approximators which can produce linguistically interpretable results. Unfortunately, their dimensionality can be extremely high due to an excessive number of inputs and rules, which raises the need for overall structure optimization. In the literature, various input selection methods are available, but they are applied separately from rule selection, often without considering the fuzzy structure. This paper proposes an integrated framework to optimize the number of inputs and the number of rules simultaneously. First, a method is developed to select the most significant rules, along with a refinement stage to remove unnecessary correlations. An improved information criterion is then proposed to find an appropriate number of inputs and rules to include in the model, leading to a balanced tradeoff between interpretability and accuracy. Simulation results confirm the efficacy of the proposed method.

Design optimization of cold-formed steel portal frames taking into account the effect of building topology

Cold-formed steel portal frames are a popular form of construction for low-rise commercial, light industrial and agricultural buildings with spans of up to 20 m. In this article, a real-coded genetic algorithm is described that is used to minimize the cost of the main frame of such buildings. The key decision variables considered in this proposed algorithm consist of both the spacing and pitch of the frame as continuous variables, as well as the discrete section sizes.A routine taking the structural analysis and frame design for cold-formed steel sections is embedded into a genetic algorithm. The results show that the real-coded genetic algorithm handles effectively the mixture of design variables, with high robustness and consistency in achieving the optimum solution. All wind load combinations according to Australian code are considered in this research. Results for frames with knee braces are also included, for which the optimization achieved even larger savings in cost.

Virtual Engineering Centre - Examples of Virtual Prototyping and Multidisciplinary Design Optimization

The requirement for the use of Virtual Engineering, encompassing the construction of Virtual Prototypes using Multidisciplinary Design Optimisation, for the development of future aerospace platforms and systems is discussed. Some of the activities at the Virtual Engineering Centre, a University of Liverpool initiative, are described and a number of case studies involving a range of applications of Virtual Engineering illustrated.

An exploration of small business Website optimization: Enablers, influencers and an assessment approach

The literature reveals a need for more integrated research contributions to small business Internet adoption and theoretical development. There is also a need for these developments to relate more closely to effective, or optimized, use of web applications in business processes and growth. To address this, and building upon recent integrated theoretical developments, the aim of this study is to explore the determinants and outcomes relating to small business Website optimization. Five determining variables isolated from recent theoretical developments relate to small business Website adoption outcomes. Utilizing an optimization rating instrument with these variables a methodological approach produced four key findings. From these findings we develop an optimization model and focus important contributions as propositions. These propositions provide a new understanding of the enablers and influencers of small business Website optimization and a basis for research to develop further insights in this area.

Optimization of an ether series of mGluR5 positive allosteric modulators: Molecular determinants of MPEP site interaction crossover

We report the optimization of a series of non-MPEP site metabotropic glutamate receptor 5 (mGlu5) pos. allosteric modulators (PAMs) based on a simple acyclic ether series. Modifications led to a gain of MPEP site interaction through incorporation of a chiral amide in conjunction with a nicotinamide core. A highly potent PAM, 8v (VU0404251), was shown to be efficacious in a rodent model of psychosis. These studies suggest that potent PAMs within topol. similar chemotypes can be developed to preferentially interact or not interact with the MPEP allosteric binding site.

Optimization of Composite Structures to Delay Mode Jump Instabilities

Numerous studies have shown that postbuckling stiffened panels may undergo abrupt changes in buckled mode
shape when loaded in uniaxial compression. This phenomenon is often referred to as a mode jump or secondary
instability. The resulting sudden release of stored energy may initiate damage in vulnerable regions within a
structure, for example, at the skin-stiffener interface of a stiffened composite panel. Current design practice is to
remove a mode jump by increasing the skin thickness of the postbuckling region. A layup optimization methodology,
based on a genetic algorithm, is presented, which delays the onset of secondary instabilities in a composite structure
while maintaining a constant weight and subject to a number of design constraints. A finite element model was
developed of a stiffened panel’s skin bay, which exhibited secondary instabilities. An automated numerical routine
extracted information directly from the finite element displacement results to detect the onset of initial buckling and
secondary instabilities. This routine was linked to the genetic algorithm to find a revised layup for the skin bay, within
appropriate design constraints, to delay the onset of secondary instabilities. The layup optimization methodology,
resulted in a panel that had a higher buckling load, prebuckling stiffness, and secondary instability load than the
baseline design.

Optimization strategy for minimizing damage in postbuckling stiffened panels

Composite materials are finding increasing use on primary aerostructures to meet demanding performance targets while reducing environmental impact. This paper presents a finite-element-based preliminary optimization methodology for postbuckling stiffened panels, which takes into account damage mechanisms that lead to delamination and subsequent failure by stiffener debonding. A global-local modeling approach is adopted in which the boundary conditions on the local model are extracted directly from the global model. The optimization procedure is based on a genetic algorithm that maximizes damage resistance within the postbuckling regime. This routine is linked to a finite element package and the iterative procedure automated. For a given loading condition, the procedure optimized the stacking sequence of several areas of the panel, leading to an evolved panel that displayed superior damage resistance in comparison with nonoptimized designs.

Multiple cutout optimization in composite plates using evolutionary structural optimization

The optimization of cutouts in composite plates was investigated by implementing a procedure known as Evolutionary Structural Optimization. Perforations were introduced into a finite element mesh of the plate from which one or more cutouts of a predetermined size were evolved. In the examples presented, plates were rejected from around each evolving cutout based on a predefined rejection criterion. The Limiting ply within each plate element around the cutout was determined based on the Tsai-Hill failure criterion. Finite element plates with values below the product of the average Tsai-Hill number and a rejection criterion were subsequently removed. This process was iterated until a steady state was reached and the rejection criterion was then incremented by an evolutionary rate and the above steps repeated until the desired cutout area was achieved. Various plates with differing lay-up and loading parameters were investigated to demonstrate the generality and robustness of this optimization procedure.