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Improving the trade-off between accuracy and interpretability is essential for the problem of handling high-dimensional data in Takagi-Sugeno-Kang (TSK) fuzzy systems and providing insights into real-world tasks. However, the TSK fuzzy system becomes complex and challenging to interpret as the data dimension increases. Here, we report an ensemble classifier, which is an enhanced adaptive network-based fuzzy inference system (ANFIS) integrating improved bagging and dropout to build concise fuzzy rule sets. First, the high-dimensional feature space is decomposed into a series of low-dimensional feature subsets using the bagging and random subspace method to train multiple ANFISs. An improved dropout strategy is then applied in training ANFISs by temporarily disabling rules in each training epoch and deleting rules after training to obtain sparse rulesets with high-quality rules. These sub-models are subsequently aggregated to perform the fuzzy inference. Results on high-dimensional benchmark datasets confirm that both the bagging and dropout strategies are effective, providing high interpretability by reducing the co-firing degrees and rules of sub-models while guaranteeing accuracy at the same time.
Fei Guo; Jiahuan Liu; Maoyuan Li; Tianlun Huang; Yun Zhang; Dequn Li; Huamin Zhou. A Concise TSK Fuzzy Ensemble Classifier Integrating Dropout and Bagging for High-dimensional Problems. IEEE Transactions on Fuzzy Systems 2021, PP, 1 -1.
AMA StyleFei Guo, Jiahuan Liu, Maoyuan Li, Tianlun Huang, Yun Zhang, Dequn Li, Huamin Zhou. A Concise TSK Fuzzy Ensemble Classifier Integrating Dropout and Bagging for High-dimensional Problems. IEEE Transactions on Fuzzy Systems. 2021; PP (99):1-1.
Chicago/Turabian StyleFei Guo; Jiahuan Liu; Maoyuan Li; Tianlun Huang; Yun Zhang; Dequn Li; Huamin Zhou. 2021. "A Concise TSK Fuzzy Ensemble Classifier Integrating Dropout and Bagging for High-dimensional Problems." IEEE Transactions on Fuzzy Systems PP, no. 99: 1-1.
Owing to their high intrinsic thermal conductivity (~2.0 W/mK), cellulose nanocrystals (CNCs) have a high potential for use as thermal management materials in modern electronics. The incorporation of a nanofiller with a high thermal conductivity, such as h-boron nitride (h-BN) and graphene (Gr), is a common approach to improve the thermal properties. However, the thermal transport across the filler–matrix interface is not well understood considering the existence of amphiphilic surfaces in the CNCs. In this study, the interfacial thermal conductance (ITC) between the hydrophobic or hydrophilic surfaces of the CNCs and h-BN was systematically investigated using molecular dynamic simulations. The hydrophobic surface exhibited the highest ITC, and the ITC for ordered CNCs was higher than that for the amorphous cellulose. The ITCs of h-BN/CNCs were higher than those of Gr/CNCs. The underlying mechanisms were explained by the interfacial adhesion strength and phonon vibration power spectrum. Additionally, the overall thermal performances of the CNCs/h-BN nanocomposites were investigated through the effective medium theory and simulation results. Although the inherent thermal conductivity of h-BN was lower than that of Gr, because of the dominant effect of the ITC on the heat transfer in the nanocomposites, h-BN with a higher ITC may increase the thermal conductivity of the CNCs more than Gr.
Maoyuan Li; Jiahuan Liu; Wenjie Yu; Yun Zhang; Huamin Zhou. Atomistic molecular dynamic simulations of the thermal transport across h-BN/cellulose nanocrystal interface. International Journal of Heat and Mass Transfer 2021, 171, 121043 .
AMA StyleMaoyuan Li, Jiahuan Liu, Wenjie Yu, Yun Zhang, Huamin Zhou. Atomistic molecular dynamic simulations of the thermal transport across h-BN/cellulose nanocrystal interface. International Journal of Heat and Mass Transfer. 2021; 171 ():121043.
Chicago/Turabian StyleMaoyuan Li; Jiahuan Liu; Wenjie Yu; Yun Zhang; Huamin Zhou. 2021. "Atomistic molecular dynamic simulations of the thermal transport across h-BN/cellulose nanocrystal interface." International Journal of Heat and Mass Transfer 171, no. : 121043.
The morphology of polymer blends plays a critical role in determining the properties of the blends and performance of resulting injection-molded parts. However, it is currently impossible to predict the morphology evolution during injection molding and the final micro-structure of the molded parts, as the existing models for the morphology evolution of polymer blends are still limited to a few simple flow fields. To fill this gap, this paper proposed a novel model for droplet morphology evolution during the mold filling process of polymer blends by coupling the models on macro- and meso-scales. The proposed model was verified by the injection molding experiment of PP/POE blends. The predicted curve of mold cavity pressure during filling process agreed precisely with the data of the corresponding pressure sensors. On the other hand, the model successfully tracked the moving trajectory and simulated morphology evolution of the droplets during the mold-filling process. After mold-filling ended, the simulation results of the final morphology of the droplets were consistent with the observations of the scanning electron microscope (SEM) experiment. Moreover, this study revealed the underlying mechanism of the droplet morphology evolution through the force analysis on the droplet. It is validated that the present model is a qualified tool for simulating the morphology evolution of polymer blends during injection molding and predicting the final microstructure of the products.
Lin Deng; Suo Fan; Yun Zhang; Zhigao Huang; Shaofei Jiang; Jiquan Li; Huamin Zhou. A Novel Multiscale Methodology for Simulating Droplet Morphology Evolution during Injection Molding of Polymer Blends. Polymers 2020, 13, 133 .
AMA StyleLin Deng, Suo Fan, Yun Zhang, Zhigao Huang, Shaofei Jiang, Jiquan Li, Huamin Zhou. A Novel Multiscale Methodology for Simulating Droplet Morphology Evolution during Injection Molding of Polymer Blends. Polymers. 2020; 13 (1):133.
Chicago/Turabian StyleLin Deng; Suo Fan; Yun Zhang; Zhigao Huang; Shaofei Jiang; Jiquan Li; Huamin Zhou. 2020. "A Novel Multiscale Methodology for Simulating Droplet Morphology Evolution during Injection Molding of Polymer Blends." Polymers 13, no. 1: 133.
Based on multiplicative decomposition of deformation gradient and energy decomposition, a temperature-dependent 3D anisotropic visco-hyperelastic constitutive model was developed for jute woven fabric reinforced poly (butylene succinate) (PBS) biocomposites for thermoforming simulation. The melted PBS matrix was characterized by a viscoelastic model, while the woven jute fabric reinforcement was modelled as an anisotropic hyperelastic material. Temperature influence on interaction between fabric reinforcement and PBS matrix was considered. A specific jute plain weave fabric reinforced PBS biocomposite was prepared and tested under thermoforming temperature range to provide a complete set of data for model parameter identification. Based on the proposed model, finite element simulation of a hemispherical thermoforming process of the biocomposite sheet was implemented. Comparison with experiment results validated the proposed constitutive model.
Jichong Wang; Xiongqi Peng; Zhigao Huang; Huaming Zhou. A temperature-dependent 3D anisotropic visco-hyperelastic constitutive model for jute woven fabric reinforced poly (butylene succinate) biocomposite in thermoforming. Composites Part B: Engineering 2020, 208, 108584 .
AMA StyleJichong Wang, Xiongqi Peng, Zhigao Huang, Huaming Zhou. A temperature-dependent 3D anisotropic visco-hyperelastic constitutive model for jute woven fabric reinforced poly (butylene succinate) biocomposite in thermoforming. Composites Part B: Engineering. 2020; 208 ():108584.
Chicago/Turabian StyleJichong Wang; Xiongqi Peng; Zhigao Huang; Huaming Zhou. 2020. "A temperature-dependent 3D anisotropic visco-hyperelastic constitutive model for jute woven fabric reinforced poly (butylene succinate) biocomposite in thermoforming." Composites Part B: Engineering 208, no. : 108584.
High filler content is the prerequisite for imparting specific properties to polymeric composite. However, serious mechanical properties degradation happened in this kind of material due to the inevitable reduction of material cohesion. In this work, highly filled poly(butylene terephthalate)/ alumina (PBT/Al2O3) composites were modified by directly melt mixing with a reactive compatibilizer ethylene–methyl acrylate–glycidyl methacrylate terpolymer (E-MA-GMA). The modified samples presented greatly enhanced elongation at break and impact response, simultaneously preserved their tensile strength and high thermal conductivity. The reactive compatibilization between PBT and Al2O3 spheres was confirmed by SEM, FTIR, and rheology characterizations. Three rheology criteria plots demonstrated that the filler percolating network and apparent yield behavior occurred in the ternary PBT/Al2O3/E-MA-GMA composites melt. It is believed that enhanced particle-matrix interfacial interaction and stress transfer caused by E-MA-GMA endowed this highly filled composite improved toughness. This study suggests the potential application of E-MA-GMA elastomer to resolve the mechanical properties degradation in highly filled polymeric composites.
Lin Jiang; Zhigao Huang; Xukang Wang; Minlong Lai; Yun Zhang; Huamin Zhou. Influence of reactive compatibilization on the mechanical, thermal and rheological properties of highly filled PBT/Al2O3 composites. Materials & Design 2020, 196, 109175 .
AMA StyleLin Jiang, Zhigao Huang, Xukang Wang, Minlong Lai, Yun Zhang, Huamin Zhou. Influence of reactive compatibilization on the mechanical, thermal and rheological properties of highly filled PBT/Al2O3 composites. Materials & Design. 2020; 196 ():109175.
Chicago/Turabian StyleLin Jiang; Zhigao Huang; Xukang Wang; Minlong Lai; Yun Zhang; Huamin Zhou. 2020. "Influence of reactive compatibilization on the mechanical, thermal and rheological properties of highly filled PBT/Al2O3 composites." Materials & Design 196, no. : 109175.
High-precision aspheric negative plastic lenses are widely used in optical systems owing to their excellent performance and ease of high-efficiency manufacturing. The imaging performance of the lens is difficult to control, because it is unable to perform optical measurements directly and is sensitive to manufacturing processing meanwhile. Generally, the imaging performance is guaranteed by a strict control of geometrical deviation, such as Peak-to-Valley (PV) and Root-Mean-Square (RMS). In this study, an optical ray-tracing algorithm with the measured geometrical deviation data is proposed to perform an imaging performance analysis correlated with geometrical deviation for the injection molded high-precision aspheric negative plastic lens. Taguchi experiments are applied to investigating the effect of processing parameters. The geometrical deviation of the convex surface is found to be an order of magnitude greater than that of the concave surface. The geometrical dimension of the concave surface is mainly determined by the machining precision of the mold cavity surface, whereas the convex surface dimension is mainly affected by the lens shrinkage. However, the imaging performance has a nonlinear correlation with the geometrical deviation. Modulation Transfer Function (MTF) and Spot Diagram are equivalently affected by the concave and convex geometrical deviations, and depend on the object field height. The effect of processing parameters on geometrical deviation and imaging performance is uncorrelated. Thus, the imaging performance should be simultaneously considered as a criterion as well as the geometrical deviation in the optimization of aspheric negative lens injection molding processing. The imaging performance prediction using an optical ray-tracing algorithm with the measured geometrical deviation data is instrumental to optimize the manufacturing processing.
Xiaowei Zhou; Yun Zhang; Wenjie Yu; Maoyuan Li; Yuhong Chen; Huamin Zhou. An imaging performance analysis method correlated with geometrical deviation for the injection molded high-precision aspheric negative plastic lens. Journal of Manufacturing Processes 2020, 58, 1115 -1125.
AMA StyleXiaowei Zhou, Yun Zhang, Wenjie Yu, Maoyuan Li, Yuhong Chen, Huamin Zhou. An imaging performance analysis method correlated with geometrical deviation for the injection molded high-precision aspheric negative plastic lens. Journal of Manufacturing Processes. 2020; 58 ():1115-1125.
Chicago/Turabian StyleXiaowei Zhou; Yun Zhang; Wenjie Yu; Maoyuan Li; Yuhong Chen; Huamin Zhou. 2020. "An imaging performance analysis method correlated with geometrical deviation for the injection molded high-precision aspheric negative plastic lens." Journal of Manufacturing Processes 58, no. : 1115-1125.
Electrochemical inhomogeneity of lithium-ion batteries stemming from heterogeneous electrode microstructure adversely affects battery rate-performance, lifetime and safety. It is attributed to manufacturing errors of electrodes in previous studies. However, the significant heterogeneous electrochemistry is still found in commercial battery electrodes with high manufacturing accuracy. Here, we propose a conjoined-electrode structure to improve the electrochemical homogeneity, in which every two adjacent cathodes or anodes are connected through microholes on current collectors. The commercial level pouch lithium-ion battery with the conjoined-electrode structure is fabricated and it displays a better rate capability (26% higher capacity at 3C rate) and a lower capacity degradation rate (decreased by 50% in the cycling tests at 1C rate). A 3-D electrochemical-thermal model is used in simulation with inhomogeneous situations to reveal the self-balancing effects of state of charge, current density, and Li-ion concentration in the conjoined-electrode structure, which facilitate more homogeneous electrochemistry in lithium-ion batteries. The limitation factor of the self-balancing effects varies depending on the structural parameters, which limits the conjoined-electrode structure design.
Ruoyu Xiong; Tengfang Zhang; Tianlun Huang; Maoyuan Li; Yun Zhang; Huamin Zhou. Improvement of electrochemical homogeneity for lithium-ion batteries enabled by a conjoined-electrode structure. Applied Energy 2020, 270, 115109 .
AMA StyleRuoyu Xiong, Tengfang Zhang, Tianlun Huang, Maoyuan Li, Yun Zhang, Huamin Zhou. Improvement of electrochemical homogeneity for lithium-ion batteries enabled by a conjoined-electrode structure. Applied Energy. 2020; 270 ():115109.
Chicago/Turabian StyleRuoyu Xiong; Tengfang Zhang; Tianlun Huang; Maoyuan Li; Yun Zhang; Huamin Zhou. 2020. "Improvement of electrochemical homogeneity for lithium-ion batteries enabled by a conjoined-electrode structure." Applied Energy 270, no. : 115109.
In this paper, the thermal behavior and process optimization for polyamide 6 during the selective laser sintering process were systematically investigated via numerical simulations and experimental testing. The effects of laser power and scanning speed were studied, and the simulation results showed that the increasing laser power and decreasing scanning speed led to the increase of the maximum temperature and the three-dimensional size of molten pool. Then, the single-layer experiments under different process parameters were carried out to verify the accuracy of the model. In addition, the energy density was applied to evaluate the combined effect of laser power and scanning speed on the thermal behavior. A process map for parameter optimization was obtained based on the predicted results, and the optimized parameters were in the region that the powder can be remelt resulting in an enough depth of molten pool, while the maximum temperature was below the decomposition temperature. Meanwhile, the specimen selected in the remelting region showed the highest tensile strength.
Maoyuan Li; Yuchen Han; Mengyuan Zhou; Peng Chen; Huang Gao; Yun Zhang; Huamin Zhou. Experimental investigating and numerical simulations of the thermal behavior and process optimization for selective laser sintering of PA6. Journal of Manufacturing Processes 2020, 56, 271 -279.
AMA StyleMaoyuan Li, Yuchen Han, Mengyuan Zhou, Peng Chen, Huang Gao, Yun Zhang, Huamin Zhou. Experimental investigating and numerical simulations of the thermal behavior and process optimization for selective laser sintering of PA6. Journal of Manufacturing Processes. 2020; 56 ():271-279.
Chicago/Turabian StyleMaoyuan Li; Yuchen Han; Mengyuan Zhou; Peng Chen; Huang Gao; Yun Zhang; Huamin Zhou. 2020. "Experimental investigating and numerical simulations of the thermal behavior and process optimization for selective laser sintering of PA6." Journal of Manufacturing Processes 56, no. : 271-279.
Simultaneous double-sided slot coating (SDSSC) has been developed to improve the efficiency of lithium-ion battery electrode production, but the coating uniformity is limited owing to the gap fluctuation caused by substrate vibration during coating the second side. Here we investigated the SDSSC with a novel contacted slot die and discussed its coating uniformity. A validated numerical model was established to describe the gap fluctuation and analyze the frequency response of coating uniformity to it. The numerical results indicate the contacted slot die can suppress the gap fluctuation to two orders of magnitude smaller than the non-contact slot die. There is a range of substrate vibration frequencies for guaranteeing the coating uniformity because it decreases with increasing frequency. In experiments with different coating thicknesses and speeds, the coating uniformities all exceeded 95% and improved upon increasing these parameters. The contacted slot die is effective at controlling coating uniformity in SDSSC.
Penghui Tan; Simian Diao; Tianlun Huang; Tengfang Zhang; Zhiming Yang; Yun Zhang; Huamin Zhou. Numerical and experimental study on coating uniformity control in simultaneous double-sided slot coating with a novel contacted slot die. Chemical Engineering Science 2020, 222, 115716 .
AMA StylePenghui Tan, Simian Diao, Tianlun Huang, Tengfang Zhang, Zhiming Yang, Yun Zhang, Huamin Zhou. Numerical and experimental study on coating uniformity control in simultaneous double-sided slot coating with a novel contacted slot die. Chemical Engineering Science. 2020; 222 ():115716.
Chicago/Turabian StylePenghui Tan; Simian Diao; Tianlun Huang; Tengfang Zhang; Zhiming Yang; Yun Zhang; Huamin Zhou. 2020. "Numerical and experimental study on coating uniformity control in simultaneous double-sided slot coating with a novel contacted slot die." Chemical Engineering Science 222, no. : 115716.
Due to its superior mechanical properties, graphene (Gr) has the potential to achieve high performance polymer-based nanocomposites. Previous studies have proved that defects in the Gr sheets could greatly reduce the mechanical properties of Gr, while the Stone-Wales (SW) defect was found to enhance the interfacial mechanical strength between Gr and epoxy. However, the combined effects of defects on the overall mechanical properties of Gr/epoxy nanocomposites have not been well understood. In this paper, the effect of the SW defect on the mechanical properties of Gr/epoxy nanocomposites was systematically investigated by using molecular dynamic simulations. The simulation results showed that the SW defect would degrade the mechanical properties of nanocomposites, including the Young’s modulus and in-plane shear modulus. Surprisingly, the transverse shear modulus could be remarkably enhanced with the existence of SW. The reinforcing mechanisms were mainly due to two aspects: (1) the SW defect could increase the surface roughness of the Gr, preventing the slippage between Gr and epoxy during the transverse shea; and (2) the nanocomposite with defective Gr enables a higher interaction energy than that with perfect graphene. Additionally, the effects of temperature, the dispersion and volume fraction of Gr were also investigated.
Maoyuan Li; Peng Chen; Bing Zheng; Tianzhengxiong Deng; Yun Zhang; Yonggui Liao; Huamin Zhou. Effect of Stone-Wales Defect on Mechanical Properties of Gr/epoxy Nanocomposites. Polymers 2019, 11, 1116 .
AMA StyleMaoyuan Li, Peng Chen, Bing Zheng, Tianzhengxiong Deng, Yun Zhang, Yonggui Liao, Huamin Zhou. Effect of Stone-Wales Defect on Mechanical Properties of Gr/epoxy Nanocomposites. Polymers. 2019; 11 (7):1116.
Chicago/Turabian StyleMaoyuan Li; Peng Chen; Bing Zheng; Tianzhengxiong Deng; Yun Zhang; Yonggui Liao; Huamin Zhou. 2019. "Effect of Stone-Wales Defect on Mechanical Properties of Gr/epoxy Nanocomposites." Polymers 11, no. 7: 1116.
In this study, the formability of woven carbon-fiber (CF)-reinforced polyether-ether-ketone (PEEK) composite sheets in the solid-state thermoforming process were investigated, and the failure mechanisms were discussed. The formability of the woven CF/PEEK sheets were analyzed using flexural tests, Erichsen test, and microscopic observation. The results show that the formability of CF/PEEK sheets significantly increases as the temperature rises from 165 to 325 °C, and slightly decreases as the deformation speed rises from 2 to 120 mm/min. The deformation of the sheets is caused by plastic deformation, shear deformation and squeeze deformation, without plastic thinning and fiber slippage, which is due to the restriction of the solid matrix and locked fibers. Moreover, the wrinkles will cause fiber fracture at lower temperatures and delamination at higher temperatures. At higher temperatures, the wrinkles mainly occur at the position with [0°/90°] fibers due to the squeezing of the matrix and fibers.
Bing Zheng; Xiping Gao; Maoyuan Li; Tianzhengxiong Deng; Zhigao Huang; Huamin Zhou; Dequn Li. Formability and Failure Mechanisms of Woven CF/PEEK Composite Sheet in Solid-State Thermoforming. Polymers 2019, 11, 966 .
AMA StyleBing Zheng, Xiping Gao, Maoyuan Li, Tianzhengxiong Deng, Zhigao Huang, Huamin Zhou, Dequn Li. Formability and Failure Mechanisms of Woven CF/PEEK Composite Sheet in Solid-State Thermoforming. Polymers. 2019; 11 (6):966.
Chicago/Turabian StyleBing Zheng; Xiping Gao; Maoyuan Li; Tianzhengxiong Deng; Zhigao Huang; Huamin Zhou; Dequn Li. 2019. "Formability and Failure Mechanisms of Woven CF/PEEK Composite Sheet in Solid-State Thermoforming." Polymers 11, no. 6: 966.
In this study, the mechanical and thermal properties of graphene were systematically investigated using molecular dynamic simulations. The effects of temperature, strain rate and defect on the mechanical properties, including Young’s modulus, fracture strength and fracture strain, were studied. The results indicate that the Young’s modulus, fracture strength and fracture strain of graphene decreased with the increase of temperature, while the fracture strength of graphene along the zigzag direction was more sensitive to the strain rate than that along armchair direction by calculating the strain rate sensitive index. The mechanical properties were significantly reduced with the existence of defect, which was due to more cracks and local stress concentration points. Besides, the thermal conductivity of graphene followed a power law of λ~L0.28, and decreased monotonously with the increase of defect concentration. Compared with the pristine graphene, the thermal conductivity of defective graphene showed a low temperature-dependent behavior since the phonon scattering caused by defect dominated the thermal properties. In addition, the corresponding underlying mechanisms were analyzed by the stress distribution, fracture structure during the deformation and phonon vibration power spectrum.
Maoyuan Li; Tianzhengxiong Deng; Bing Zheng; Yun Zhang; Yonggui Liao; Huamin Zhou. Effect of Defects on the Mechanical and Thermal Properties of Graphene. Nanomaterials 2019, 9, 347 .
AMA StyleMaoyuan Li, Tianzhengxiong Deng, Bing Zheng, Yun Zhang, Yonggui Liao, Huamin Zhou. Effect of Defects on the Mechanical and Thermal Properties of Graphene. Nanomaterials. 2019; 9 (3):347.
Chicago/Turabian StyleMaoyuan Li; Tianzhengxiong Deng; Bing Zheng; Yun Zhang; Yonggui Liao; Huamin Zhou. 2019. "Effect of Defects on the Mechanical and Thermal Properties of Graphene." Nanomaterials 9, no. 3: 347.
Efficiency and accuracy are critical in the motion control of a batch process. This paper proposes a new intelligent motion control method for a batch process based on reinforcement learning (RL) and iterative learning control (ILC). The proposed learning-based motion control method enables the system to learn from its previous experience. The motion control method can be divided into two parts: (1) RL-based trajectory optimization and (2) ILC-based positioning control. Experiments were conducted to demonstrate the effectiveness of the proposed method. The results indicate that the proposed method not only reduces the process time effectively while ensuring system stability, but also achieves excellent positioning accuracy.
Yufei Ruan; Yun Zhang; Ting Mao; Xundao Zhou; Dequn Li; Huamin Zhou. Trajectory optimization and positioning control for batch process using learning control. Control Engineering Practice 2019, 85, 1 -10.
AMA StyleYufei Ruan, Yun Zhang, Ting Mao, Xundao Zhou, Dequn Li, Huamin Zhou. Trajectory optimization and positioning control for batch process using learning control. Control Engineering Practice. 2019; 85 ():1-10.
Chicago/Turabian StyleYufei Ruan; Yun Zhang; Ting Mao; Xundao Zhou; Dequn Li; Huamin Zhou. 2019. "Trajectory optimization and positioning control for batch process using learning control." Control Engineering Practice 85, no. : 1-10.
In this study, the flexural behavior and fracture mechanisms of short carbon fiber reinforced polyether-ether-ketone (SCFR/PEEK) composites at various ambient temperatures were investigated. First, the crystallinity and glass transition temperature (Tg) of PEEK and SCFR/PEEK were analyzed by differential scanning calorimetry analysis and dynamic mechanical analysis tests, respectively. The addition of SCFs increases the Tg but does not change the crystallinity of the PEEK matrix. Then, the three-point flexural tests of PEEK and SCFR/PEEK were performed over the temperature range of 20 to 235 °C, and the temperature-dependencies of the flexural properties of PEEK and SCFR/PEEK were discussed in detail. Finally, the microstructure of SCFR/PEEK was observed using a digital microscope and scanning electron microscope. The results show that the tension crack occurs first, and the crack extends upward leading to the shear crack and compression crack at room temperature. The fracture of SCFR/PEEK is mainly due to the extraction and rupture of SCFs. At high temperatures (above Tg), the tension crack and compression crack both occur, and the strong ductility of the matrix prevents the generation of shear crack. The fracture of SCFR/PEEK is mainly due to the rotation and extraction of SCFs, while the SCFs rupture plays a minor role.
Bing Zheng; Tianzhengxiong Deng; Maoyuan Li; Zhigao Huang; Huamin Zhou; Dequn Li. Flexural Behavior and Fracture Mechanisms of Short Carbon Fiber Reinforced Polyether-Ether-Ketone Composites at Various Ambient Temperatures. Polymers 2018, 11, 18 .
AMA StyleBing Zheng, Tianzhengxiong Deng, Maoyuan Li, Zhigao Huang, Huamin Zhou, Dequn Li. Flexural Behavior and Fracture Mechanisms of Short Carbon Fiber Reinforced Polyether-Ether-Ketone Composites at Various Ambient Temperatures. Polymers. 2018; 11 (1):18.
Chicago/Turabian StyleBing Zheng; Tianzhengxiong Deng; Maoyuan Li; Zhigao Huang; Huamin Zhou; Dequn Li. 2018. "Flexural Behavior and Fracture Mechanisms of Short Carbon Fiber Reinforced Polyether-Ether-Ketone Composites at Various Ambient Temperatures." Polymers 11, no. 1: 18.
Tianlun Huang; Penghui Tan; Maoyuan Li; Yun Zhang; Huamin Zhou. Numerical modeling and analysis of heat transfer for floatation nozzle with a flexible substrate. International Journal of Thermal Sciences 2018, 137, 665 -674.
AMA StyleTianlun Huang, Penghui Tan, Maoyuan Li, Yun Zhang, Huamin Zhou. Numerical modeling and analysis of heat transfer for floatation nozzle with a flexible substrate. International Journal of Thermal Sciences. 2018; 137 ():665-674.
Chicago/Turabian StyleTianlun Huang; Penghui Tan; Maoyuan Li; Yun Zhang; Huamin Zhou. 2018. "Numerical modeling and analysis of heat transfer for floatation nozzle with a flexible substrate." International Journal of Thermal Sciences 137, no. : 665-674.
Feature learning is a generic and fundamental problem in data-based process monitoring of batch processes, such as injection molding. This paper proposes an automatic feature learning method, considering the following two vital characteristic aspects: the mechanical characteristics within a batch and the inherent characteristics among batches. Unsupervised feature learning is performed using convolution-deconvolution auto encoders, and the learned features are applied as predefined parameters for process monitoring, including process condition identification and fault detection. Experiments are carried out with different process conditions. The results indicate that the proposed method achieves improved model generalization ability under various process conditions, which means it can precisely reveal the variable autocorrelations and cross-correlations among different variables. Meanwhile, the learned features achieve higher classification accuracies and offer more optimal solutions for process monitoring. This method has been proven as an efficient means of feature learning, which should be appropriate for other batch processes.
Ting Mao; Yun Zhang; Yufei Ruan; Huang Gao; Huamin Zhou; Dequn Li. Feature learning and process monitoring of injection molding using convolution-deconvolution auto encoders. Computers & Chemical Engineering 2018, 118, 77 -90.
AMA StyleTing Mao, Yun Zhang, Yufei Ruan, Huang Gao, Huamin Zhou, Dequn Li. Feature learning and process monitoring of injection molding using convolution-deconvolution auto encoders. Computers & Chemical Engineering. 2018; 118 ():77-90.
Chicago/Turabian StyleTing Mao; Yun Zhang; Yufei Ruan; Huang Gao; Huamin Zhou; Dequn Li. 2018. "Feature learning and process monitoring of injection molding using convolution-deconvolution auto encoders." Computers & Chemical Engineering 118, no. : 77-90.
Elapsed time is always one of the most important performance measures for polymer injection moulding simulation. Solving pressure correction equations is the most time-consuming part in the mould filling simulation using finite volume method with SIMPLE-like algorithms. Algebraic multigrid (AMG) is one of the most promising methods for this type of elliptic equations. It, thus, has better performance by contrast with some common one-level iterative methods, especially for large problems. And it is also suitable for parallel computing. However, AMG is not easy to be applied due to its complex theory and poor generality for the large range of computational fluid dynamics applications. This paper gives a robust and efficient parallel AMG solver, A1-pAMG, for 3D mould filling simulation of injection moulding. Numerical experiments demonstrate that, A1-pAMG has better parallel performance than the classical AMG, and also has algorithmic scalability in the context of 3D unstructured problems.
Zixiang Hu; Yun Zhang; Junjie Liang; Songxin Shi; Huamin Zhou. An efficient parallel algebraic multigrid method for 3D injection moulding simulation based on finite volume method. International Journal of Computational Fluid Dynamics 2014, 28, 316 -328.
AMA StyleZixiang Hu, Yun Zhang, Junjie Liang, Songxin Shi, Huamin Zhou. An efficient parallel algebraic multigrid method for 3D injection moulding simulation based on finite volume method. International Journal of Computational Fluid Dynamics. 2014; 28 (6-10):316-328.
Chicago/Turabian StyleZixiang Hu; Yun Zhang; Junjie Liang; Songxin Shi; Huamin Zhou. 2014. "An efficient parallel algebraic multigrid method for 3D injection moulding simulation based on finite volume method." International Journal of Computational Fluid Dynamics 28, no. 6-10: 316-328.
Injection velocity profile is an important process parameter that affects the quality of injection-molded parts. In this paper, a fast optimization method for injection velocity profile is proposed, which aims at a constant melt-front-velocity throughout the filling stage. According to the relationship between cavity geometry and the melt-front-velocity, the ideal injection velocity is proportional to the melt-front-area. Through studying the filling behavior of molten polymer and the characteristic of 3D surface mesh model, a modified Dijkstra's algorithm is employed to predict the melt-front-area at different filling steps. Based on the predicted melt-front-area, a least square method is adopted to find out the optimum injection velocity profile by minimizing the difference of injection velocity and the ideal injection velocity. Finally, a short shot experiment and a Moldflow simulation experiment have been conducted to verify the proposed optimization method, which demonstrate that the proposed method is correct and effective.
Peng Zhao; Ding Yang; Huamin Zhou; Kai Xu. Fast Optimization of Injection Velocity Profile Based on Graph Theory. Polymer-Plastics Technology and Engineering 2011, 50, 581 -587.
AMA StylePeng Zhao, Ding Yang, Huamin Zhou, Kai Xu. Fast Optimization of Injection Velocity Profile Based on Graph Theory. Polymer-Plastics Technology and Engineering. 2011; 50 (6):581-587.
Chicago/Turabian StylePeng Zhao; Ding Yang; Huamin Zhou; Kai Xu. 2011. "Fast Optimization of Injection Velocity Profile Based on Graph Theory." Polymer-Plastics Technology and Engineering 50, no. 6: 581-587.
In injection moulding production, the tuning of the process parameters is a challenging job, which relies heavily on the experience of skilled operators. In this paper, taking into consideration operator assessment during moulding trials, a novel intelligent model for automated tuning of process parameters is proposed. This consists of case based reasoning (CBR), empirical model (EM), and fuzzy logic (FL) methods. CBR and EM are used to imitate recall and intuitive thoughts of skilled operators, respectively, while FL is adopted to simulate the skilled operator optimization thoughts. First, CBR is used to set up the initial process parameters. If CBR fails, EM is employed to calculate the initial parameters. Next, a moulding trial is performed using the initial parameters. Then FL is adopted to optimize these parameters and correct defects repeatedly until the moulded part is found to be satisfactory. Based on the above methodologies, intelligent software was developed and embedded in the controller of an injection moulding machine. Experimental results show that the intelligent software can be effectively used in practical production, and it greatly reduces the dependence on the experience of the operators.
Peng Zhao; Jian-Zhong Fu; Hua-Min Zhou; Shu-Biao Cui. Automated process parameters tuning for an injection moulding machine with soft computing. Journal of Zhejiang University-SCIENCE A 2011, 12, 201 -206.
AMA StylePeng Zhao, Jian-Zhong Fu, Hua-Min Zhou, Shu-Biao Cui. Automated process parameters tuning for an injection moulding machine with soft computing. Journal of Zhejiang University-SCIENCE A. 2011; 12 (3):201-206.
Chicago/Turabian StylePeng Zhao; Jian-Zhong Fu; Hua-Min Zhou; Shu-Biao Cui. 2011. "Automated process parameters tuning for an injection moulding machine with soft computing." Journal of Zhejiang University-SCIENCE A 12, no. 3: 201-206.
CAD and CAE have now become very popular in injection molding development. Integration with virtual reality is a new boost to these fields. This paper presents a research effort targeting the creation of a desktop-based, low-cost and independent virtual injection molding system, which is implemented based on the techniques such as virtual reality, finite element analysis, motion simulation and scientific visualization. With the stereoscopic display of the mold design and motion, the system provides engineers a cohesive view of mold structure and assembly. And by analyzing the numerical CAE results, the possible faults during molding process can also be highlighted. With this integration, the overall system would be a new powerful tool to mimic the real process of injection molding and evaluate various influences from product design to manufacturing, capable, therefore, of improving the moldability and the quality of molded products.
Huamin Zhou; Songxin Shi; Bin Ma. A virtual injection molding system based on numerical simulation. The International Journal of Advanced Manufacturing Technology 2009, 40, 297 -306.
AMA StyleHuamin Zhou, Songxin Shi, Bin Ma. A virtual injection molding system based on numerical simulation. The International Journal of Advanced Manufacturing Technology. 2009; 40 (3-4):297-306.
Chicago/Turabian StyleHuamin Zhou; Songxin Shi; Bin Ma. 2009. "A virtual injection molding system based on numerical simulation." The International Journal of Advanced Manufacturing Technology 40, no. 3-4: 297-306.