Narrow Results

In this paper we address the problem of accurately estimating the runtime and communication time of a client request in a Network Enabled Server (NES) middleware such as GridSolve. We use a template based model for the runtime estimation and a client-server communication test for the transfer time estimation. We implement these two mechanisms in GridSolve and test them on a real testbed. Experiments show that they allow for significant improvement in terms of client execution time on various scenarios.

The design and optimization of substructure of a floating offshore wind turbines (FOWT) is an extremely challengeable work. Before this work, it is necessary to investigate the correlation of design variables of the FOWT substructure. The correlation analysis can help to reduce the dimensions of design parameters and output results, and provide insight into the nature of the design space. The subsequent design and optimization workload can therefore be reduced. This paper aims to provide a framework of parametric modeling and correlation analysis of the substructure design variables for a single-column FOWT with a slack catenary mooring system. The NREL offshore 5 MW baseline wind turbine is selected in this study, and various floating foundation configurations are designed to adapt to this wind turbine. In order to evaluate the main dynamic performances of the FOWT well and quickly, a reduced-degree-of-freedom model of the FOWT is constructed and verified. Then, the substructure design parameters are parameterized to facilitate modeling, and simulations based on design of experiments are performed to save evaluation time and cost. In simulations, three sets of steady wind speeds are applied to eliminate the influence of controller dynamics. The results showed that the correlation of dynamic performances of the FOWT is significant, indicating that it is enough to consider several outputs to represent the dynamic behavior of the system. Regarding the designing parameters, the draft generates the most significant influence on the FOWT dynamic performances. The column radius has different influences for the cases with and without heave plates. Additionally, whether or not the heave plate is added, the mooring line length mainly influences the 95th percentile of platform horizontal surge displacement and standard deviation of fairlead tension of the downwind mooring line.

This work aimed at investigating the influence of Baguera and Discocerv cervical disc prostheses, with mobile downward center of rotation (COR) and fixed upward COR, respectively, on the biomechanical behavior of C4–C6 cervical spine. For this purpose, using computed tomography (CT) data, a parametric nonlinear finite element (FE) model of intact C4–C6 spinal segments was developed, and an artificial disc was implanted at C5–C6 level. To assess the influence of implants on the biomechanics of cervical spine, the FE models were analyzed in flexion, extension, lateral bending, and axial rotation, and the results were presented in the range of motion (ROM) curves, and torsional stiffness. Results of this study, in agreement with the literature, suggested that both Baguera and Discocerv implants might be able to preserve the motion, and limit the alteration of the biomechanics of adjacent levels. Except for the possible confliction of adjacent vertebrae at the implanted level with Baguera implant in lateral bending, results of this study also indicated that the movability and downward COR of Baguera disc prosthesis caused ROMs of the implanted segment to be more similar to the intact model than Discocerv implant. Moreover, the upward COR of Discocerv implant may result in over-distraction on facets in the maximal flexion, with the ratio of 1.22 versus 1.36, and consequently facet syndrome during extension for Bageura and Discocerv disc prostheses, respectively.

This chapter provides an overview of parametric modeling of microwave components using combined neural network and transfer function (neuro-transfer function or neuro-TF). Transfer functions are used to represent the electromagnetic (EM) responses of passive components versus frequency. With the help of the transfer function, the nonlinearity of the neural network structure can be significantly decreased. We first introduce the neuro-TF modeling approach in rational format. Following that, we review the recent neuro-TF modeling approach in pole/zero format, where a pole/zero-matching algorithm is needed for addressing the issue of mismatch of poles and zeros before training the overall neuro-TF model. The neuro-TF modeling technique in pole/residue format is also reviewed. The orders of the pole–residue transfer functions may vary over different regions of geometrical parameters. A pole–residue tracking technique can be used to solve this order-changing problem. As a further advancement, we discuss the sensitivity analysis-based neuro-TF modeling technique. The purpose is to increase the model accuracy by utilizing EM sensitivity information and to speed up the model development process by reducing the number of training data required for developing the model. After the modeling process, the trained model can be used to provide accurate and fast prediction of the EM responses with respect to the geometrical variables and can be subsequently used in the high-level circuit and system design.

In order to conduct the lightweight design of the twist beam of passenger car rear suspension, the loads applied on the twist beam under typical four load cases were determined based on dynamic simulation. The topological optimization model of the twist beam was built up and then used to acquire the optimal topology structure according to variable density method. Furthermore, mesh morphing software Meshworks/Morpher was employed to build parametric model of the twist beam, which was used to define six design variables for fully parameterizing the cross section. Then the multi-island genetic algorithm (MIGA) was adopted to perform the multi-objective optimization for the lightweight design of the twist beam, where the mass and maximum deformation were defined as the objective functions while the strength, torsional stiffness and main mode frequencies were taken as constraints. The optimization results indicate that the mass of the lightweight twist beam is significantly reduced from 8.0kg to 6.25kg, with weight reduction of 21.9%, whilst its low-order natural vibration characteristics, strength, maximum deformation and torsional stiffness have basically unchanged. This also demonstrated that the proposed design method in this paper is effective and feasible.