Papers by Keyword: Optimization Technique

Abstract: Finite element (FE) model updating of structures using vibration test data has received considerable attentions in recent years due to its crucial role in fields ranging from establishing a reality-consistent structural model for dynamic analysis and control, to providing baseline model for damage identification in structural health monitoring. Model updating is to correct the analytical finite element model using test data to produce a refined one that better predict the dynamic behavior of structure. However, for real complex structures, conventional updating methods is difficult to be utilized to update the FE model of structures due to the heavy computational burden for the dynamic analysis. Meta-model is an effective surrogate model for dynamic analysis of large-scale structures. An updating method based on the combination between meta-model and component mode synthesis (CMS) is proposed to improve the efficiency of model updating of large-scale structures. The effectiveness of the proposed method is then validated by updating a scaled suspender arch bridge model using the simulated data.

Abstract: This paper collects the main methodologies and tools employed for predicting the surface roughness. The goal of this work is to provide compact and adequate information that could be useful in metal cutting industries to select the techniques and optimization tools that best suit to their needs and particular requirements. Each approach, with its advantages and disadvantages, is outlined and the present and future trends are discussed. As result, a quick guide for using practitioners of mentioned industrial sector is provided in form of tables that relate: machining parameters, cutting tool properties, workpiece properties and cutting phenomena with the different techniques and optimization tools usually employed to analyze the different parameters and phenomena involved in the process of surface roughness generation.

Abstract: This paper evaluates the performance of acoustic beam forming using ultrasonic transducers. A directional audible sound can be generated by amplitude-modulating the ultrasound carrier with an audio signal, then transmitting it from an array of ultrasonic transducers. A novel method has been proposed in this paper to control the beam width of the main lobe and the level of the side lobe for the beam pattern by using an optimization technique. Furthermore, the weighting distribution of uniform linear array composed of eight transducers and the effect of different weightings on the spreading angle of the sound beam have been investigated through simulations in this study. The results show that the optimization method proposed in the paper can effectively control the beam width of the main lobe and the level of the side lobe for the audible sound.

Abstract: Purpose – The objective of this study is to investigate the effect of various parameters on rapid prototyping parts for processes of sintering metallic powder by using fiber laser via the design of experiments (DOE) method. Design/methodology/approach – Experiments based on the DOE method were utilized to determine an optimal parameter setting for achieving a minimum amount of porosities in specimens during the selective laser sintering (SLS) process. Analysis of variance (ANOVA) was further conducted to identify significant factors. Findings – A regression model predicting percentages of porosities under various conditions was developed when the traditional Taguchi’s approach failed to identify a feasible model due to strong interactions of controlled factors. The significant factors to the process were identified by ANOVA. Research limitations/implications – Four controlled factors including pulse frequencies and scan rate of laser beams, laser power and scan line spacing with particle sizes of 5µm of the powder base material had significant influence on the sintering process. Future investigation planned to be carried out for achieving multiple quality targets such as the hardness and the density for 3D parts. Originality/value – The implementation of the DOE method provided a systematic approach to identify an optimal parameter setting of the SLS process; thus, the efficiency of designing optimal parameters was greatly improved. This approach could be easily extended to 3D cases by just including additional parameters into the design. Additionally, utilization of the normality analysis on the residual data ensured that the selected model was adequate and extracted all applicable information from the experimental data.

Abstract: In this study, we present an experimental/numerical methodology which aims to improve 3D thin sheet hydroforming. The experimental study is dedicated to the identification of stress-strain flow by using the Nelder-Mead simplex algorithm optimization from the global measure of displacement and force. Applications are made to the simulation of thin sheet hydroforming using different die geometry to show the efficiency of the proposed methodology to localize plastic instability, thinning of the blanks and damage initiation under different forming condition.

Abstract: High efficient cutting process technique is one of the main development directions of cutting process technology in the future, a reasonable choice of NC machining cutting parameter is an important way to realize high efficiency NC machining. NC machining cutting parameter optimization techniques were studied, using BP neural network, milling parameters optimization model of aluminum alloy shell structure was built, and the structure of BP neural network was analysed, realizing the optimizing of the BP neural network model, the improving of the convergence accuracy, convergence speed, prediction accuracy, generalization ability of BP neural network model, which optimized the cutting parameters selection and predicted the processing efficiency to provide a theoretical basis for the selection of high efficiency NC machining cutting parameter. Production practice showed: the application of the optimized cutting parameters of BP neural network for processing could improve processing efficiency, reduce costs notablely while guaranteeing the processing quality, and achieve the optimization of integrated application efficiency for high efficiency NC machining and NC machine, so it has a higher promotional value.

Abstract: This paper presents the design of a novel superconducting levitated module for UAQ4 train whose feasibility has been successfully tested and confirmed in laboratory. The work concept of self-balancing “V” shaped levitation module is described and the results of levitation tests performed using a measurement set up are discussed. Lastly the levitation module performances are also carried out using numerical finite element analyses by varying the sideslip angle of the module and work system configuration.

Abstract: Finite element model updating of structures usually ends up with a nonlinear optimization problem. An efficient optimization technique is proposed firstly, which draws together the global searching capability of chaos-based optimization technique and high searching efficiency of trust-region Newton method. This hybrid approach is demonstrated to be more efficient and prone to global minimum than conventional gradient search methods and random search methods by testifying with three test functions. The optimization problem for model updating using modal frequencies and modal shapes is formulated, and a procedure to update the boundary support parameters is presented. A modal test was conducted on a beam structure, and the identified mode frequencies are employed to formulate the optimization problem with the support parameters as the updating parameters. The discrepancy between the mode frequencies of the finite element models before and after updating is greatly reduced, and the updated support condition meet quite well with the insight to the devices that form the supports.

Abstract: This work presents a motion planning approach for tomato harvesting manipulators with seven degrees of freedom (7 DOF) based on an optimization technique and alternative method. It is to find optimal joint perturbations during the path planning so that a manipulator reaches a goal from an initial position with high accuracy. The optimization model consists of the objective function defined by the tracking error and the representation of a set of mathematical relationships that describe the kinematic restrictions of the manipulator. In this method, only a forward kinematics is used and the complex mathematics in numerical solutions of an inverse kinematics is avoided to reduce the computation load. Simulation results show that the tomato harvesting manipulator can move the end-effector to the target from an initial position along a specified geometric trajectory in its workspace. Simultaneously, the joint displacements vary smoothly within their limits during tracking. The position absolute error, moving velocity and precision of the end-effector are 0.53mm, 0.18m/s and 3.75% respectively, which fulfill the requirements of tomato picking with well working efficiency.

Abstract: In order to evaluate the variation of fatigue data of turbine blade steel in low pressure (LP) steam, it is important to estimate probabilistic stress-life (P-S-N) curve to accurately define the probability distribution. In this study, a new procedure was introduced to determine the expression of P-S-N curves. For this purpose, 3-parameter Weibull distribution was found to be the most appropriate among assumed distributions when the probability distributions of the fatigue life were examined by a comparative analysis. Furthermore, the parameter of P-S-N curve was evaluated using various optimization techniques to maximize the correlation coefficient. As a result, the sequential linear program method is used for estimation of P-S-N curve.