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Proc. ASME. CIE92, ASME 1992 International Computers in Engineering Conference: Volume 1 — Artificial Intelligence; Expert Systems; CAD/CAM/CAE; Computers in Fluid Mechanics/Thermal Systems, 69-74, August 2–6, 1992

Paper No: CIE1992-0009

DOI: https://doi.org/10.1115/CIE1992-0009

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Topics: Artificial neural networks, Design, Computer software, Neural network models, User interfaces

Proceedings Papers

Associative Transformation of Query Words for Case Retrieval System Based on Neural Network

Shigeru Nagasawa, Yasushi Fukuzawa, Yasunori Miyata, Hiroshi Hasegawa, Hiroshi Sakuta

Proc. ASME. DETC99, Volume 2: 19th Computers and Information in Engineering Conference, 483-489, September 12–16, 1999

Paper No: DETC99/CIE-9062

DOI: https://doi.org/10.1115/DETC99/CIE-9062

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Topics: Artificial neural networks, Finite element analysis, Databases, Engines, Filtration, Indexing (Machining), Neural network models, Teaching

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

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

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

Proceedings Papers

Comparing Attribute- and Form-Based Machine Learning Techniques for Component Prediction

Glen Williams, Lucas Puentes, Jacob Nelson, Jessica Menold, Conrad Tucker, Christopher McComb

Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A019, August 17–19, 2020

Paper No: DETC2020-22256

DOI: https://doi.org/10.1115/DETC2020-22256

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Topics: Machine learning, Algorithms, Gears, Engineers, Neural network models, Sales, Three-dimensional models

Proceedings Papers

An Automatic Interaction Method Using Part Recognition Based on Deep Network for Augmented Reality Assembly Guidance

Xuyue Yin, Xiumin Fan, Jiajie Wang, Rui Liu, Qiang Wang

Proc. ASME. IDETC-CIE2018, Volume 1B: 38th Computers and Information in Engineering Conference, V01BT02A018, August 26–29, 2018

Paper No: DETC2018-85810

DOI: https://doi.org/10.1115/DETC2018-85810

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Topics: Manufacturing, Artificial neural networks, Neural network models

Proceedings Papers

Basic Study on Development of Delight Design Method: Proposal and Application of Beer Cup Design Based on Value Model and Evaluation Model of KANSEI

Yukako Tanaka, Mai Misaka, Hideki Aoyama

Proc. ASME. IDETC-CIE2017, Volume 1: 37th Computers and Information in Engineering Conference, V001T02A042, August 6–9, 2017

Paper No: DETC2017-68089

DOI: https://doi.org/10.1115/DETC2017-68089

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Topics: Design, Design methodology, Ceramics, Fracture (Materials), Neural network models, Preferences, Product design, Product quality

Proceedings Papers

The Layout Measurement Points Prediction and Flatness Calculation for the Antenna Plate After Welding Assembly Based on the RBF Neural Network Model

Minghui Pan, Wencheng Tang, Yan Xing, Jun Ni

Proc. ASME. IDETC-CIE2016, Volume 4: 21st Design for Manufacturing and the Life Cycle Conference; 10th International Conference on Micro- and Nanosystems, V004T05A001, August 21–24, 2016

Paper No: DETC2016-59041

DOI: https://doi.org/10.1115/DETC2016-59041

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Topics: Manufacturing, Neural network models, Welding, Artificial neural networks, Fittings

Proceedings Papers

Meta-Modeling for Enhancing Design Optimization of Electric Motors

Wei Ji, Xiaolong Feng, Jonas Larsson, Alexander Stening, Freddy Gyllensten, Hongliang Yang

Proc. ASME. IDETC-CIE2016, Volume 2B: 42nd Design Automation Conference, V02BT03A026, August 21–24, 2016

Paper No: DETC2016-59356

DOI: https://doi.org/10.1115/DETC2016-59356

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Topics: Design, Electric motors, Modeling, Optimization, Motors, Algorithms, Dimensions, Engineering simulation, Neural network models, Performance

Proceedings Papers

Hybrid Simulation of a Dynamic Multibody Vehicle Suspension System Using Neural Network Modeling Fit of Tire Data

John Dye, Hamid Lankarani

Proc. ASME. IDETC-CIE2016, Volume 6: 12th International Conference on Multibody Systems, Nonlinear Dynamics, and Control, V006T09A036, August 21–24, 2016

Paper No: DETC2016-60435

DOI: https://doi.org/10.1115/DETC2016-60435

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Topics: Artificial neural networks, Modeling, Simulation, Suspension systems, Tires, Vehicles, Dynamics (Mechanics), Wheels, Roads, Steady state

Proceedings Papers

Ensemble Neural Network Model for Predicting the Energy Consumption of a Milling Machine

Ronay Ak, Moneer M. Helu, Sudarsan Rachuri

Proc. ASME. IDETC-CIE2015, Volume 4: 20th Design for Manufacturing and the Life Cycle Conference; 9th International Conference on Micro- and Nanosystems, V004T05A056, August 2–5, 2015

Paper No: DETC2015-47957

DOI: https://doi.org/10.1115/DETC2015-47957

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Topics: Energy consumption, Milling machines, Neural network models, Milling, Uncertainty, Accounting, Artificial neural networks, Drilling, Machining, Manufacturing systems

Proceedings Papers

Research on Surrogate Model Based on Local Radial Point Interpolation Method

Rongqiao Wang, Jianxing Mao, Dianyin Hu

Proc. ASME. IDETC-CIE2015, Volume 10: ASME 2015 Power Transmission and Gearing Conference; 23rd Reliability, Stress Analysis, and Failure Prevention Conference, V010T12A003, August 2–5, 2015

Paper No: DETC2015-46689

DOI: https://doi.org/10.1115/DETC2015-46689

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Topics: Interpolation, Polynomials, Event history analysis, Construction, Gas turbines, Neural network models, Robustness, Shapes

Proceedings Papers

Vibration Control of Cylindrical Shell Panel With Shape Memory Alloy Actuators

Huiyu Li, Hua Li, H. S. Tzou

Proc. ASME. IDETC-CIE2013, Volume 8: 22nd Reliability, Stress Analysis, and Failure Prevention Conference; 25th Conference on Mechanical Vibration and Noise, V008T13A084, August 4–7, 2013

Paper No: DETC2013-12788

DOI: https://doi.org/10.1115/DETC2013-12788

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Topics: Actuators, Pipes, Shape memory alloys, Vibration control, Artificial neural networks, Temperature, Neural network models, Vibration, Wire, Heating

Proceedings Papers

Deformation Prediction of Mouse Embryos in Cell Injection Experiment by a Feedforward Artificial Neural Network

Ali A. Abbasi, M. T. Ahmadian, G. R. Vossoughi

Proc. ASME. IDETC-CIE2011, Volume 2: 31st Computers and Information in Engineering Conference, Parts A and B, 543-550, August 28–31, 2011

Paper No: DETC2011-47073

DOI: https://doi.org/10.1115/DETC2011-47073

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Topics: Artificial neural networks, Deformation, Feedforward control, Mechanical behavior, Neural network models, Cell membranes, Modeling, Sensitivity analysis

Proceedings Papers

Neural Network Bushing Model Development Using Simulation

Jennifer L. Johrendt, Peter R. Frise

Proc. ASME. IDETC-CIE2010, Volume 4: 12th International Conference on Advanced Vehicle and Tire Technologies; 4th International Conference on Micro- and Nanosystems, 101-109, August 15–18, 2010

Paper No: DETC2010-28103

DOI: https://doi.org/10.1115/DETC2010-28103

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Topics: Artificial neural networks, Bushings, Model development, Simulation, Engineering prototypes, Manufacturing, Neural network models, Data acquisition, Deflection, Rubber

Proceedings Papers

Performance Comparison of Metamodeling Methods From the Perspective of Sample Quality Merits

Dong Zhao, Deyi Xue

Proc. ASME. IDETC-CIE2009, Volume 5: 35th Design Automation Conference, Parts A and B, 699-709, August 30–September 2, 2009

Paper No: DETC2009-86270

DOI: https://doi.org/10.1115/DETC2009-86270

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Topics: Neural network models, Noise (Sound), Performance evaluation, Polynomials, Robustness

Proceedings Papers

Robust Optimization of an Automotive Valvetrain Using a Multiobjective Genetic Algorithm

Emre Kazancioglu, Guangquan Wu, Jeonghan Ko, Stanislav Bohac, Zoran Filipi, S. Jack Hu, Dennis Assanis, Kazuhiro Saitou

Proc. ASME. IDETC-CIE2003, Volume 2: 29th Design Automation Conference, Parts A and B, 97-108, September 2–6, 2003

Paper No: DETC2003/DAC-48714

DOI: https://doi.org/10.1115/DETC2003/DAC-48714

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Topics: Genetic algorithms, Optimization, Engines, Automobiles, Design, Dimensions, Fuel consumption, Horsepower, Neural network models, Pareto optimization

Proceedings Papers

Performance Optimization of Extrusion Blow Molded Parts Using Fuzzy Neural-Taguchi Method and Genetic Algorithm

Jyh-Cheng Yu, Tsung-Ren Hung, Francis Thibault

Proc. ASME. IDETC-CIE2002, Volume 2: 28th Design Automation Conference, 133-139, September 29–October 2, 2002

Paper No: DETC2002/DAC-34047

DOI: https://doi.org/10.1115/DETC2002/DAC-34047

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Topics: Extruding, Genetic algorithms, Optimization, Design, Computer programming, Molding, Simulation, Stress, Computer software, Finite element analysis

NARROW

Design Form and Function Prediction From a Single Image

Pattern Matching Synthesis As an Automated Approach to Mechanism Design

Development of a Design Tool Incorporating Neural Networks

Associative Transformation of Query Words for Case Retrieval System Based on Neural Network

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

Comparing Attribute- and Form-Based Machine Learning Techniques for Component Prediction

An Automatic Interaction Method Using Part Recognition Based on Deep Network for Augmented Reality Assembly Guidance

Basic Study on Development of Delight Design Method: Proposal and Application of Beer Cup Design Based on Value Model and Evaluation Model of KANSEI

The Layout Measurement Points Prediction and Flatness Calculation for the Antenna Plate After Welding Assembly Based on the RBF Neural Network Model

Meta-Modeling for Enhancing Design Optimization of Electric Motors

Hybrid Simulation of a Dynamic Multibody Vehicle Suspension System Using Neural Network Modeling Fit of Tire Data

Ensemble Neural Network Model for Predicting the Energy Consumption of a Milling Machine

Research on Surrogate Model Based on Local Radial Point Interpolation Method

Vibration Control of Cylindrical Shell Panel With Shape Memory Alloy Actuators

Deformation Prediction of Mouse Embryos in Cell Injection Experiment by a Feedforward Artificial Neural Network

Neural Network Bushing Model Development Using Simulation

Performance Comparison of Metamodeling Methods From the Perspective of Sample Quality Merits

Robust Optimization of an Automotive Valvetrain Using a Multiobjective Genetic Algorithm

Performance Optimization of Extrusion Blow Molded Parts Using Fuzzy Neural-Taguchi Method and Genetic Algorithm

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