Optimal design of composite laminates for minimizing delamination stresses by particle swarm optimization combined with FEM

Jianqiao Chen,Wenjie Peng,Junhong Wei,Rui Ge 국제구조공학회 2009 Structural Engineering and Mechanics, An Int'l Jou Vol.31 No.4

The present paper addresses the optimal design of composite laminates with the aim of minimizing free-edge delamination stresses. A technique involving the application of particle swarm optimization (PSO) integrated with FEM was developed for the optimization. Optimization was also conducted with the zero-order method (ZOM) included in ANSYS. The semi-analytical method, which provides an approximation of the interlaminar normal stress of laminates under in-plane load, was used to partially validate the optimization results. It was found that optimal results based on ZOM are sensitive to the starting design points, and an unsuitable initial design set will lead to a result far from global solution. By contrast, the proposed method can find the global optimal solution regardless of initial designs, and the solutions were better than those obtained by ZOM in all the cases investigated.

Fuzzy reliability analysis of laminated composites

Chen, Jianqiao,Wei, Junhong,Xu, Yurong Techno-Press 2006 Structural Engineering and Mechanics, An Int'l Jou Vol.22 No.6

The strength behaviors of Fiber Reinforced Plastics (FRP) Composites can be greatly influenced by the properties of constitutive materials, the laminate structures, and load conditions etc, accompanied by many uncertainty factors. So the reliability study on FRP is an important subject of research. Many achievements have been made in reliability studies based on the probability theory, but little has been done on the roles played by fuzzy variables. In this paper, a fuzzy reliability model for FRP laminates is established first, in which the loads are considered as random variables and the strengths as fuzzy variables. Then a numerical model is developed to assess the fuzzy reliability. The Monte Carlo simulation method is utilized to compute the reliability of laminas under the maximum stress criterion. In the second part of this paper, a generalized fuzzy reliability model (GFRM) is proposed. By virtue of the fact that there may exist a series of states between the failure state and the function state, a fuzzy assumption for the structure state together with the probabilistic assumption for strength parameters is adopted to construct the GFRM of composite materials. By defining a generalized limit state function, the problem is converted to the conventional reliability formula that enables the first-order reliability method (FORM) applicable in calculating the reliability index. Several examples are worked out to show the validity of the models and the efficiency of the methods proposed in this paper. The parameter sensitivity analysis shows that some of the mean values of the strength parameters have great influence on the laminated composites' reliability. The differences resulting from the application of different failure criteria and different fuzzy assumptions are also discussed. It is concluded that the GFRM is feasible to use, and can provide an effective and synthetic method to evaluate the reliability of a system with different types of uncertainty factors.

Modified Constraint Scores for Semi-Supervised Feature Selection

Jianqiao Wang,Yuehua Li,Kun Chen 보안공학연구지원센터 2014 International Journal of Signal Processing, Image Vol.7 No.5

Semi-supervised constraint scores, which utilize both pairwise constraints and the local property of the unlabeled data to select features, achieve comparable performance to the supervised feature selection methods. The local property is characterized without considering the pairwise constraints and these two conditions are introduced independently. However, the pairwise constraints and the local property may contain conflicting information. In this paper, we utilize the conflicting information to improve the local property. Instead of characterizing the local property by all neighbors, samples which do not appear in the cannot-link constraints can be used. A performance indicator, called neighborhood-cannot-link (NC) coefficient, is proposed to measure the improvement of the local property. We use the improved local property and the pairwise constraints to perform semi-supervised constraint scores algorithm. Experiments on several real world data sets demonstrate the effectiveness of the methods.

Fuzzy reliability analysis of laminated composites

Jianqiao Chen,Junhong Wei,Yurong Xu 국제구조공학회 2006 Structural Engineering and Mechanics, An Int'l Jou Vol.22 No.6

Optimal design of composite laminates for minimizing delamination stresses by particle swarm optimization combined with FEM

Chen, Jianqiao,Peng, Wenjie,Ge, Rui,Wei, Junhong Techno-Press 2009 Structural Engineering and Mechanics, An Int'l Jou Vol.31 No.4

The present paper addresses the optimal design of composite laminates with the aim of minimizing free-edge delamination stresses. A technique involving the application of particle swarm optimization (PSO) integrated with FEM was developed for the optimization. Optimization was also conducted with the zero-order method (ZOM) included in ANSYS. The semi-analytical method, which provides an approximation of the interlaminar normal stress of laminates under in-plane load, was used to partially validate the optimization results. It was found that optimal results based on ZOM are sensitive to the starting design points, and an unsuitable initial design set will lead to a result far from global solution. By contrast, the proposed method can find the global optimal solution regardless of initial designs, and the solutions were better than those obtained by ZOM in all the cases investigated.

A novel multi-objective tuning strategy for model predictive control in trajectory tracking

Jianqiao Chen,Guofu Tian,Yanbo Fu 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.12

Accuracy and efficiency are two important performances of model predictive control in trajectory tracking and they are seriously affected by the control parameters of model predictive control. To make the model predictive control with high accuracy and efficiency simultaneous, the paper proposed a strategy to tune the control parameters for model predictive control. The proposed strategy converts the tuning problem to a multi-objective optimization problem and employs non-dominated sorting genetic algorithm (NSGA-II) to solve it. The proposed strategy is employed to tune the control parameters for a classical model predictive control in a typical trajectory tracking condition. The simulation results show that the comprehensive performances of model predictive controller tuned by the proposed method are better than other tuning methods. The proposed tuning strategy is validated and it can be applied to tune the control parameters for model predictive control in trajectory tracking.

System Simulation Modeling for Near-field Millimeter Wave Synthetic Aperture Imaging Radiometer

Jianfei Chen,Yuehua Li,Jianqiao Wang,Yuanjiang Li 보안공학연구지원센터(IJSIP) 2014 International Journal of Signal Processing, Image Vol.7 No.6

Due to the fact that theoretical analysis and instrument construction for antenna array of synthetic aperture imaging radiometer (SAIR) are both complicated, and designers usually hope to predict the imaging effect and analysis the influence of relevant parameters of SAIR before the system design. The imaging simulation is a very useful method in the system design of SAIR. This paper is devoted to establishing an accurate imaging model for simulating the process of near-field millimeter wave SAIR. In this model, the target radiation signals and received signals of receivers are represented by the accurate signals in the time domain, which improves the efficiency of this simulation model significantly. The visibility function is collected by the cross-correlation between I/Q signals of the antenna pairs just as the imaging process of the practical SAIR. Some characteristics (such as the coherence between targets, the resolution and no-aliasing FOV of SAIR and so on) are verified by the corresponding 1D and 2D simulation experiments, and the effectiveness of this imaging model is also tested by these simulation experiments. The simulation experiment results show that this model is an efficient, accurate imaging simulation model, and can be employed in the system design of near-field millimeter wave SAIR.

Catalytic performance of CuCl2-modified V2O5-WO3/TiO2 catalyst for Hg0 oxidation in simulated flue gas

Chuanmin Chen,Wenbo Jia,Songtao Liu,Yue Cao,Bing Zhao,Jianqiao Wang 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.3

CuCl2-SCR catalysts prepared by an improved impregnation method were studied to evaluate the catalytic performance for gaseous elemental mercury (Hg0) oxidation in simulated flue gas. Hg0 oxidation activity of commercial SCR catalyst was significantly improved by the introduction of CuCl2. Nitrogen adsorption, XRD, XRF and XPS were used to characterize the catalysts. The results indicated that CuCl2 was well loaded and highly dispersed on the catalyst surface, and that CuCl2 played an important role for Hg0 catalytic oxidation. The effects of individual flue gas components on Hg0 oxidation were also investigated over CuCl2-SCR catalyst at 350 oC. The co-presence of NO and NH3 remarkably inhibited Hg0 oxidation, while this inhibiting effect was gradually scavenged with the decrease of GHSV. Further study revealed the possibility of simultaneous removal of Hg0 and NO over CuCl2-SCR catalyst in simulated flue gas. The mechanism of Hg0 oxidation was also investigated.