Page 1 | Search Results | ASME Digital Collection

Skip to Main Content

Skip Nav Destination

1-20 of 22

1

Sort by

Sort Order Select

Journal Articles

Three-Dimensional-Slice-Super-Resolution-Net: A Fast Few Shooting Learning Model for 3D Super-Resolution Using Slice-Up and Slice-Reconstruction

Hongbin Lin, Qingfeng Xu, Handing Xu, Yanjie Xu, Yiming Zheng, Yubin Zhong, Zhenguo Nie

Publisher: ASME

J. Comput. Inf. Sci. Eng. January 2024, 24(1): 011005.

Paper No: JCISE-23-1027

https://doi.org/10.1115/1.4063275

Published Online: September 14, 2023

View Article titled, Three-Dimensional-Slice-Super-Resolution-Net: A Fast Few Shooting Learning Model for 3D Super-Resolution Using Slice-Up and Slice-Reconstruction

Topics: Resolution (Optics)

Journal Articles

Cross-Domain Transfer Learning for Galvanized Steel Strips Defect Detection and Recognition

Hao Chen, Hongbin Lin, Qingfeng Xu, Yaguan Li, Yiming Zheng, Jianghua Fei, Kang Yang, Wenhui Fan, Zhenguo Nie

Publisher: ASME

J. Comput. Inf. Sci. Eng. January 2024, 24(1): 011006.

Paper No: JCISE-23-1026

https://doi.org/10.1115/1.4063102

Published Online: September 14, 2023

View Article titled, Cross-Domain Transfer Learning for Galvanized Steel Strips Defect Detection and Recognition

Topics: Flaw detection, Manufacturing, Steel, Strips, Galvanized steel, Design, Feature extraction, Inspection

Journal Articles

Intelligent Detection and Classification of Surface Defects on Cold-Rolled Galvanized Steel Strips Using a Data-Driven Faulty Model With Attention Mechanism

Hao Chen, Zhenguo Nie, Qingfeng Xu, Jianghua Fei, Kang Yang, Yaguan Li, Hongbin Lin, Wenhui Fan, Xin-Jun Liu

J. Comput. Inf. Sci. Eng. August 2023, 23(4): 041001.

Paper No: JCISE-22-1207

https://doi.org/10.1115/1.4055672

Published Online: December 27, 2022

View Article titled, Intelligent Detection and Classification of Surface Defects on Cold-Rolled Galvanized Steel Strips Using a Data-Driven Faulty Model With Attention Mechanism

Topics: Flaw detection, Galvanized steel, Steel, Strips

Proceedings Papers

Classification of Surface Defects on Galvanized Cold-Rolled Steel Sheets Using Data-Driven Fault Model With Attention Mechanism

Hao Chen, Zhenguo Nie, Qingfeng Xu, Jianghua Fei, Kang Yang, Yaguan Li, Wenhui Fan, Xin-Jun Liu

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A075, August 14–17, 2022

Paper No: DETC2022-91218

https://doi.org/10.1115/DETC2022-91218

View Paper titled, Classification of Surface Defects on Galvanized Cold-Rolled Steel Sheets Using Data-Driven Fault Model With Attention Mechanism

Topics: Steel sheet, Assembly lines, Galvanized steel, Inspection, Metal stamping, Quality control, Steel

Journal Articles

SuperMeshing: Boosting the Mesh Density of Stress Field in Plane-Strain Problems Using Deep Learning Method

Handing Xu, Zhenguo Nie, Qingfeng Xu, Yaguan Li, Fugui Xie, Xin-Jun Liu

J. Comput. Inf. Sci. Eng. June 2023, 23(3): 034501.

Paper No: JCISE-21-1402

https://doi.org/10.1115/1.4054687

Published Online: August 8, 2022

View Article titled, SuperMeshing: Boosting the Mesh Density of Stress Field in Plane-Strain Problems Using Deep Learning Method

Topics: Density, Stress, Plane strain, Finite element methods, Resolution (Optics)

Proceedings Papers

SuperMeshing: A Deep Learning Method for Boosting Mesh Density in Numerical Computation Within 2D Domain

Handing Xu, Zhenguo Nie, Qingfeng Xu, Xinjun Liu

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A037, August 17–19, 2021

Paper No: DETC2021-68112

https://doi.org/10.1115/DETC2021-68112

View Paper titled, SuperMeshing: A Deep Learning Method for Boosting Mesh Density in Numerical Computation Within 2D Domain

Topics: Computation, Density, Stress, Finite element methods, Resolution (Optics), Artificial neural networks, Errors, Interpolation, Plane strain

Proceedings Papers

SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Metal Forming Stress Field With Attention Mechanism And Perceptual Features

Qingfeng Xu, Zhenguo Nie, Handing Xu, Haosu Zhou, Xinjun Liu

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A041, August 17–19, 2021

Paper No: DETC2021-71158

https://doi.org/10.1115/DETC2021-71158

View Paper titled, SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Metal Forming Stress Field With Attention Mechanism And Perceptual Features

Topics: Density, Metalworking, Stress, Finite element analysis, Errors, Finite element methods, Interpolation, Sheet metal work, Simulation results

Journal Articles

SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Physical Fields in Metal Forming Numerical Simulation

Qingfeng Xu, Zhenguo Nie, Handing Xu, Haosu Zhou, Hamid Reza Attar, Nan Li, Fugui Xie, Xin-Jun Liu

J. Appl. Mech. January 2022, 89(1): 011002.

Paper No: JAM-21-1240

https://doi.org/10.1115/1.4052195

Published Online: September 13, 2021

View Article titled, SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Physical Fields in Metal Forming Numerical Simulation

Topics: Density, Finite element methods, Metalworking, Interpolation, Resolution (Optics)

Journal Articles

A Study on Using Image-Based Machine Learning Methods to Develop Surrogate Models of Stamp Forming Simulations

Haosu Zhou, Qingfeng Xu, Zhenguo Nie, Nan Li

J. Manuf. Sci. Eng. February 2022, 144(2): 021012.

Paper No: MANU-21-1029

https://doi.org/10.1115/1.4051604

Published Online: August 6, 2021

View Article titled, A Study on Using Image-Based Machine Learning Methods to Develop Surrogate Models of Stamp Forming Simulations

Topics: Design, Engineering simulation, Finite element analysis, Machine learning, Multilayer perceptron, Scalars, Simulation, Interpolation, Metalworking, Simulation results

Journal Articles

StressGAN: A Generative Deep Learning Model for Two-Dimensional Stress Distribution Prediction

Haoliang Jiang, Zhenguo Nie, Roselyn Yeo, Amir Barati Farimani, Levent Burak Kara

J. Appl. Mech. May 2021, 88(5): 051005.

Paper No: JAM-20-1553

https://doi.org/10.1115/1.4049805

Published Online: February 11, 2021

View Article titled, StressGAN: A Generative Deep Learning Model for Two-Dimensional Stress Distribution Prediction

Topics: Stress, Stress concentration, Geometry, Boundary-value problems

Journal Articles

TopologyGAN: Topology Optimization Using Generative Adversarial Networks Based on Physical Fields Over the Initial Domain

Zhenguo Nie, Tong Lin, Haoliang Jiang, Levent Burak Kara

J. Mech. Des. March 2021, 143(3): 031715.

Paper No: MD-20-1434

https://doi.org/10.1115/1.4049533

Published Online: February 3, 2021

View Article titled, TopologyGAN: Topology Optimization Using Generative Adversarial Networks Based on Physical Fields Over the Initial Domain

Topics: Generators, Optimization, Stress, Topology, Boundary-value problems, Design, Displacement

Proceedings Papers

StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction

Haoliang Jiang, Zhenguo Nie, Roselyn Yeo, Amir Barati Farimani, Levent Burak Kara

Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A023, August 17–19, 2020

Paper No: DETC2020-22682

https://doi.org/10.1115/DETC2020-22682

View Paper titled, StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction

Topics: Stress concentration, Stress, Boundary-value problems, Geometry, Artificial neural networks, Computation, Neural network models, Performance, Physics, Resolution (Optics)

Proceedings Papers

TopologyGAN: Topology Optimization Using Generative Adversarial Networks Based on Physical Fields Over the Initial Domain

Zhenguo Nie, Tong Lin, Haoliang Jiang, Levent Burak Kara

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A008, August 17–19, 2020

Paper No: DETC2020-22675

https://doi.org/10.1115/DETC2020-22675

View Paper titled, TopologyGAN: Topology Optimization Using Generative Adversarial Networks Based on Physical Fields Over the Initial Domain

Topics: Optimization, Topology, Boundary-value problems, Errors, Generators, Design, Excitation, Network models, Stress

Journal Articles

Optimization of Part Consolidation for Minimum Production Costs and Time Using Additive Manufacturing

Zhenguo Nie, Sangjin Jung, Levent Burak Kara, Kate S. Whitefoot

J. Mech. Des. July 2020, 142(7): 072001.

Paper No: MD-19-1214

https://doi.org/10.1115/1.4045106

Published Online: December 12, 2019

View Article titled, Optimization of Part Consolidation for Minimum Production Costs and Time Using Additive Manufacturing

Topics: Additive manufacturing, Design, Filters, Manufacturing, Optimization, Tradeoffs, Shades and shadows, Genetic algorithms, Metals

Includes: Supplementary data

Proceedings Papers

Optimization of Parts Consolidation for Minimum Production Costs and Time Using Additive Manufacturing

Zhenguo Nie, Sangjin Jung, Levent Burak Kara, Kate S. Whitefoot

Proc. ASME. IDETC-CIE2019, Volume 2A: 45th Design Automation Conference, V02AT03A032, August 18–21, 2019

Paper No: DETC2019-97649

https://doi.org/10.1115/DETC2019-97649

View Paper titled, Optimization of Parts Consolidation for Minimum Production Costs and Time Using Additive Manufacturing

Topics: Additive manufacturing, Optimization, Manufacturing, Filters, Redundancy (Engineering), Aircraft, Cathode ray oscilloscopes, Electron beams, Energy consumption, Genetic algorithms

Proceedings Papers

Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks

Zhenguo Nie, Haoliang Jiang, Levent Burak Kara

Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A011, August 18–21, 2019

Paper No: DETC2019-98472

https://doi.org/10.1115/DETC2019-98472

View Paper titled, Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks

Topics: Artificial neural networks, Stress

Journal Articles

Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks

Zhenguo Nie, Haoliang Jiang, Levent Burak Kara

J. Comput. Inf. Sci. Eng. February 2020, 20(1): 011002.

Paper No: JCISE-19-1077

https://doi.org/10.1115/1.4044097

Published Online: September 10, 2019

View Article titled, Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks

Topics: Stress, Artificial neural networks, Geometry, Testing

Journal Articles

A Coupled Thermomechanical Modeling Method for Predicting Grinding Residual Stress Based on Randomly Distributed Abrasive Grains

Zhenguo Nie, Gang Wang, Liping Wang, Yiming (Kevin) Rong

J. Manuf. Sci. Eng. August 2019, 141(8): 081005.

Paper No: MANU-19-1006

https://doi.org/10.1115/1.4043799

Published Online: June 10, 2019

View Article titled, A Coupled Thermomechanical Modeling Method for Predicting Grinding Residual Stress Based on Randomly Distributed Abrasive Grains

Topics: Grinding, Stress, Thermomechanics, Temperature, Simulation

Journal Articles

A Statistical Model of Equivalent Grinding Heat Source Based on Random Distributed Grains

Zhenguo Nie, Gang Wang, Dehao Liu, Yiming (Kevin) Rong

J. Manuf. Sci. Eng. May 2018, 140(5): 051016.

Paper No: MANU-17-1572

https://doi.org/10.1115/1.4038729

Published Online: March 7, 2018

View Article titled, A Statistical Model of Equivalent Grinding Heat Source Based on Random Distributed Grains

Topics: Grinding, Heat, Temperature, Heat flux

Proceedings Papers

Numerical Simulation of the Austenitizing Process in Hypoeutectoid Fe-C Steels

Dehao Liu, Gang Wang, Zhenguo Nie, Yiming (Kevin) Rong

Proc. ASME. MSEC2014, Volume 1: Materials; Micro and Nano Technologies; Properties, Applications and Systems; Sustainable Manufacturing, V001T01A004, June 9–13, 2014

Paper No: MSEC2014-3948

https://doi.org/10.1115/MSEC2014-3948

View Paper titled, Numerical Simulation of the Austenitizing Process in Hypoeutectoid Fe-C Steels

Topics: Computer simulation, Steel, Phase transitions, Diffusion (Physics), Ferrites (Magnetic materials), Heating, Particulate matter, Temperature

1