The Experts below are selected from a list of 278268 Experts worldwide ranked by ideXlab platform
Han-xiong Huang - One of the best experts on this subject based on the ideXlab platform.
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optimizing parison thickness for extrusion blow molding by Hybrid Method
Journal of Materials Processing Technology, 2007Co-Authors: Gengqun Huang, Han-xiong HuangAbstract:Abstract A Hybrid Method consisting of finite element Method (FEM), artificial neural network (ANN), and genetic algorithm (GA) was used to find the optimal parison thickness distribution for a blow molded part with required thickness distribution. Firstly, numerical simulations on the parison inflation were performed using FEM and the K-BKZ integral type constitutive equation. Based on the simulation results, a back propagation (BP) ANN model was then developed to build the relationship between parison thickness distribution and the objective function, which was used to evaluate the wall thickness distribution of part. The predictive ability of the ANN model was verified through FEM simulation results different from those utilized in the training stage. Finally, a GA was developed and used to search for the optimal parison thickness distribution. The results showed that the Hybrid Method proposed in this work can effectively obtain the optimal parison thickness distribution for a blow molded part with required wall thickness distribution. Compared with the trial and error Method, the Hybrid Method can shorten the part development time and save a lot of material.
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optimizing parison thickness for extrusion blow molding by Hybrid Method
Journal of Materials Processing Technology, 2007Co-Authors: Gengqun Huang, Han-xiong HuangAbstract:Abstract A Hybrid Method consisting of finite element Method (FEM), artificial neural network (ANN), and genetic algorithm (GA) was used to find the optimal parison thickness distribution for a blow molded part with required thickness distribution. Firstly, numerical simulations on the parison inflation were performed using FEM and the K-BKZ integral type constitutive equation. Based on the simulation results, a back propagation (BP) ANN model was then developed to build the relationship between parison thickness distribution and the objective function, which was used to evaluate the wall thickness distribution of part. The predictive ability of the ANN model was verified through FEM simulation results different from those utilized in the training stage. Finally, a GA was developed and used to search for the optimal parison thickness distribution. The results showed that the Hybrid Method proposed in this work can effectively obtain the optimal parison thickness distribution for a blow molded part with required wall thickness distribution. Compared with the trial and error Method, the Hybrid Method can shorten the part development time and save a lot of material.
Gengqun Huang - One of the best experts on this subject based on the ideXlab platform.
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optimizing parison thickness for extrusion blow molding by Hybrid Method
Journal of Materials Processing Technology, 2007Co-Authors: Gengqun Huang, Han-xiong HuangAbstract:Abstract A Hybrid Method consisting of finite element Method (FEM), artificial neural network (ANN), and genetic algorithm (GA) was used to find the optimal parison thickness distribution for a blow molded part with required thickness distribution. Firstly, numerical simulations on the parison inflation were performed using FEM and the K-BKZ integral type constitutive equation. Based on the simulation results, a back propagation (BP) ANN model was then developed to build the relationship between parison thickness distribution and the objective function, which was used to evaluate the wall thickness distribution of part. The predictive ability of the ANN model was verified through FEM simulation results different from those utilized in the training stage. Finally, a GA was developed and used to search for the optimal parison thickness distribution. The results showed that the Hybrid Method proposed in this work can effectively obtain the optimal parison thickness distribution for a blow molded part with required wall thickness distribution. Compared with the trial and error Method, the Hybrid Method can shorten the part development time and save a lot of material.
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optimizing parison thickness for extrusion blow molding by Hybrid Method
Journal of Materials Processing Technology, 2007Co-Authors: Gengqun Huang, Han-xiong HuangAbstract:Abstract A Hybrid Method consisting of finite element Method (FEM), artificial neural network (ANN), and genetic algorithm (GA) was used to find the optimal parison thickness distribution for a blow molded part with required thickness distribution. Firstly, numerical simulations on the parison inflation were performed using FEM and the K-BKZ integral type constitutive equation. Based on the simulation results, a back propagation (BP) ANN model was then developed to build the relationship between parison thickness distribution and the objective function, which was used to evaluate the wall thickness distribution of part. The predictive ability of the ANN model was verified through FEM simulation results different from those utilized in the training stage. Finally, a GA was developed and used to search for the optimal parison thickness distribution. The results showed that the Hybrid Method proposed in this work can effectively obtain the optimal parison thickness distribution for a blow molded part with required wall thickness distribution. Compared with the trial and error Method, the Hybrid Method can shorten the part development time and save a lot of material.
Monika Swami - One of the best experts on this subject based on the ideXlab platform.
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strong convergence of a Hybrid Method for infinite family of nonexpansive mapping and variational inequality
Journal of the Indonesian Mathematical Society, 2021Co-Authors: Savita Rathee, Monika SwamiAbstract:The motivation behind this paper is to use Hybrid Method for searching a typical component of the set of fixed point of an infinite family of non expansive mapping and the set of monotone, Lipschtiz continuous variational inequality problem. The contemplated Method is combination of two Method one is extragradient Method and the other one is DQ Method. Also, we demonstrate the strong convergence of the designed iterative technique, under some warm conditions.
Gaurav Khanna - One of the best experts on this subject based on the ideXlab platform.
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a multi domain Hybrid Method for head on collision of black holes in particle limit
International Journal of Modern Physics C, 2011Co-Authors: Debananda Chakraborty, Jaehun Jung, Gaurav KhannaAbstract:A Hybrid Method is developed based on the spectral and finite-difference Methods for solving the inhomogeneous Zerilli equation in time-domain. The developed Hybrid Method decomposes the domain into the spectral and finite-difference domains. The singular source term is located in the spectral domain while the solution in the region without the singular term is approximated by the higher-order finite-difference Method. The spectral domain is also split into multi-domains and the finite-difference domain is placed as the boundary domain. Due to the global nature of the spectral Method, a multi-domain Method composed of the spectral domain only does not yield the proper power-law decay unless the range of the computational domain is large. The finite-difference domain helps reduce boundary effects due to the truncation of the computational domain. The multi-domain approach with the finite-difference boundary domain Method reduces the computational cost significantly and also yields the proper power-law decay. Stable and accurate interface conditions between the finite-difference and spectral domains and the spectral and spectral domains are derived. For the singular source term, we use both the Gaussian model with various values of full width at half-maximum and a localized discrete δ-function. The discrete δ-function was generalized to adopt the Gauss–Lobatto collocation points of the spectral domain. The gravitational waveforms are measured. Numerical results show that the developed Hybrid Method accurately yields the quasi-normal modes and the power-law decay profile. The numerical results also show that the power-law decay profile is less sensitive to the shape of the regularized δ-function for the Gaussian model than expected. The Gaussian model also yields better results than the localized discrete δ-function.
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a multi domain Hybrid Method for head on collision of black holes in particle limit
arXiv: Computational Physics, 2011Co-Authors: Debananda Chakraborty, Jaehun Jung, Gaurav KhannaAbstract:A Hybrid Method is developed based on the spectral and finite-difference Methods for solving the inhomogeneous Zerilli equation in time-domain. The developed Hybrid Method decomposes the domain into the spectral and finite-difference domains. The singular source term is located in the spectral domain while the solution in the region without the singular term is approximated by the higher-order finite-difference Method. The spectral domain is also split into multi-domains and the finite-difference domain is placed as the boundary domain. Due to the global nature of the spectral Method, a multi-domain Method composed of the spectral domains only does not yield the proper power-law decay unless the range of the computational domain is large. The finite-difference domain helps reduce boundary effects due to the truncation of the computational domain. The multi-domain approach with the finite-difference boundary domain Method reduces the computational costs significantly and also yields the proper power-law decay. Stable and accurate interface conditions between the finite-difference and spectral domains and the spectral and spectral domains are derived. For the singular source term, we use both the Gaussian model with various values of full width at half maximum and a localized discrete $\delta$-function. The discrete $\delta$-function was generalized to adopt the Gauss-Lobatto collocation points of the spectral domain. The gravitational waveforms are measured. Numerical results show that the developed Hybrid Method accurately yields the quasi-normal modes and the power-law decay profile. The numerical results also show that the power-law decay profile is less sensitive to the shape of the regularized $\delta$-function for the Gaussian model than expected. The Gaussian model also yields better results than the localized discrete $\delta$-function.
Jie Cheng - One of the best experts on this subject based on the ideXlab platform.
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an efficient Hybrid Method for estimating clear sky surface downward longwave radiation from modis data
Journal of Geophysical Research, 2017Co-Authors: Jie Cheng, Shunlin Liang, Wenhui Wang, Yamin GuoAbstract:This paper proposes an efficient Hybrid Method for estimating 1 km instantaneous clear-sky surface downward longwave radiation (LWDN) from Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared observations and the MODIS near-infrared column water vapor (CWV) data product. The LWDN was formulated as a nonlinear function of surface upwelling longwave radiation estimated from the MODIS top-of-atmosphere (TOA) radiance of channels 29, 31, and 32, as well as CWV and the MODIS TOA radiance of channel 29. Ground measurements collected at 62 globally distributed sites from six networks were used to develop and validate the proposed Hybrid Method. The validation results showed that the bias and root-mean-square error (RMSE) were 0.0597 W/m2 and 21.008 W/m2. These results demonstrate that the performance of our Method is superior to that of other studies reported in the literature. The drawback of our Method is that LWDN is overestimated over high-elevation areas with extremely low CWV (<0.5 g/cm2) and underestimated over regions with tropical climates that have extremely high CWV. A power function relating LWDN to CWV was derived and used as a complementary Method to address these circumstances. The overestimation was overcome, and the bias and RMSE decreased from 9.407 W/m2 and 23.919 W/m2 to −0.924 W/m2 and 19.895 W/m2. The underestimation was also alleviated.
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estimating clear sky land surface longwave upwelling radiation from modis data using a Hybrid Method
Journal of remote sensing, 2016Co-Authors: Aixiu Nie, Qiang Liu, Jie ChengAbstract:Surface longwave upwelling radiation LWUP is one of the four components for calculating the earth’s surface radiation budget. Under the general framework of the Hybrid Method, we developed linear models for estimating the global 1-km instantaneous clear-sky LWUP from the top-of-atmosphere TOA radiance of the Moderate Resolution Imaging Spectroradiometer MODIS thermal infrared channels 29, 31, and 32. Extensive radiative transfer simulations were conducted to produce a large number of representative samples, from which the linear model was derived. The derived Hybrid model was first evaluated using ground measurements collected at 15 sites from two networks SURFRAD and ASRCOP. According to the validation results, the average bias and root mean square error RMSE of −0.55 and 15.76 W m−2, respectively, were obtained by averaging the mean bias and RMSE for the two networks. Compared to a Hybrid Method developed by a previous study and the temperature-emissivity Method, our linear model had a superior performance.
