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Proceedings Papers

A New Approach to Develop an Intelligent Robotic Gripper Using Virtual Tools Implementing IIoT and ML Technologies

David Guerra-Zubiaga, Logan Block, Adam Ricketts, Jacob Faile, Charlie Dickson

Proc. ASME. IMECE2021, Volume 2B: Advanced Manufacturing, V02BT02A009, November 1–5, 2021

Paper No: IMECE2021-69993

DOI: https://doi.org/10.1115/IMECE2021-69993

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Topics: Design, End effectors, Grippers, Internet of things, Machine learning, Manufacturing, Computers, Decision making, Engineers, Robotics

Proceedings Papers

A New Approach to Develop an Intelligent Manufacturing System Using Virtual Tools

David Guerra-Zubiaga, Corey Morton, Derrick Stacey, Virginia Peach, Chan Ham, Diego Escobar Escobar, Noah Hitchcock

Proc. ASME. IMECE2021, Volume 2B: Advanced Manufacturing, V02BT02A016, November 1–5, 2021

Paper No: IMECE2021-71546

DOI: https://doi.org/10.1115/IMECE2021-71546

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Topics: Internet of things, Machine learning, Manufacturing, Manufacturing systems, Manufacturing tools, Simulation

Proceedings Papers

A Machine Learning Approach for Predicting Melt-Pool Dynamics of Ti-6Al-4V Alloy in the Laser Powder-Bed Fusion Process

M. Shafiqur Rahman, Jonathan Ciaccio, Uttam K. Chakravarty

Proc. ASME. IMECE2021, Volume 4: Advances in Aerospace Technology, V004T04A025, November 1–5, 2021

Paper No: IMECE2021-71348

DOI: https://doi.org/10.1115/IMECE2021-71348

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Topics: Alloys, Dynamics (Mechanics), Lasers, Machine learning

Proceedings Papers

Ultrasonic Characterization of Biomimetic Porous Scaffold Using Machine Learning: Application of Biot’s Theory

Mohammad Hodaei, Pooneh Maghoul

Proc. ASME. IMECE2021, Volume 1: Acoustics, Vibration, and Phononics, V001T01A012, November 1–5, 2021

Paper No: IMECE2021-72746

DOI: https://doi.org/10.1115/IMECE2021-72746

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Topics: Biomimetics, Fluids, Machine learning, Waves

Proceedings Papers

Study on Underwater Friction Stir Welded AA 2024-T3 Pipes Using Machine Learning Algorithms

Ibrahim Sabry, Abdel-Hamid I. Mourad, Dinu Thomas Thekkuden

Proc. ASME. IMECE2021, Volume 2A: Advanced Manufacturing, V02AT02A033, November 1–5, 2021

Paper No: IMECE2021-71378

DOI: https://doi.org/10.1115/IMECE2021-71378

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Topics: Algorithms, Artificial neural networks, Friction, Machine learning, Pipes, Welding

Proceedings Papers

Digital Twin: Universal User Interface for Online Management of the Manufacturing System

Vladimir Kuts, Yevhen Bondarenko, Marietta Gavriljuk, Andriy Paryshev, Sergei Jegorov, Simone Pizzagall, Tauno Otto

Proc. ASME. IMECE2021, Volume 2B: Advanced Manufacturing, V02BT02A003, November 1–5, 2021

Paper No: IMECE2021-69092

DOI: https://doi.org/10.1115/IMECE2021-69092

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Topics: Manufacturing systems, Mobile robots, Robots, User interfaces, Computer software, Machinery, Simulation, Manufacturing, Computer programming, Design

Proceedings Papers

Intelligent Process Control Following Industry 4.0 Trends

David Guerra-Zubiaga, Grayson McMichael, Diana Segura-Velandia, Maria Aslam, Seung-Woo Yim, Zack Anderson, Yee Mey Goh

Proc. ASME. IMECE2021, Volume 2B: Advanced Manufacturing, V02BT02A002, November 1–5, 2021

Paper No: IMECE2021-68686

DOI: https://doi.org/10.1115/IMECE2021-68686

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Topics: Internet of things, Machine learning, Manufacturing, Process control, Data collection, Feedback, Process control systems

Proceedings Papers

Application of Data Processing and Machine Learning Techniques for In Situ Monitoring of Metal Additive Manufacturing Using Acoustic Emission Data

Md Shahjahan Hossain, Hossein Taheri

Proc. ASME. IMECE2021, Volume 2B: Advanced Manufacturing, V02BT02A041, November 1–5, 2021

Paper No: IMECE2021-68835

DOI: https://doi.org/10.1115/IMECE2021-68835

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Topics: Acoustic emissions, Additive manufacturing, Artificial neural networks, Machine learning, Metals, Nondestructive evaluation, Wavelets

Proceedings Papers

Deformation Manifold Learning Model for Deformation of Multi-Walled Carbon Nano-Tubes: Exploring the Latent Space

Upendra Yadav, Shashank Pathrudkar, Susanta Ghosh

Proc. ASME. IMECE2021, Volume 12: Mechanics of Solids, Structures, and Fluids; Micro- and Nano- Systems Engineering and Packaging, V012T12A010, November 1–5, 2021

Paper No: IMECE2021-70463

DOI: https://doi.org/10.1115/IMECE2021-70463

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Topics: Carbon nanotubes, Deformation, Manifolds, Machine learning, Multi-walled carbon nanotubes, Physics, Artificial neural networks, Principal component analysis, Atoms, Design

Proceedings Papers

Applied Machine Learning Method to Predict Crack Propagation Path in Polycrystalline Graphene Sheet

Mohan S. R. Elapolu, Md. Imrul Reza Shishir, Alireza Tabarraei

Proc. ASME. IMECE2021, Volume 12: Mechanics of Solids, Structures, and Fluids; Micro- and Nano- Systems Engineering and Packaging, V012T12A011, November 1–5, 2021

Paper No: IMECE2021-70543

DOI: https://doi.org/10.1115/IMECE2021-70543

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Topics: Crack propagation, Graphene, Machine learning

Proceedings Papers

A Nonlinear Finite Element-Based Supervised Machine Learning Approach for Efficiently Predicting Collapse Resistance of Wireline Tool Housings Subjected to Combined Loads

Fei Song, Kevin Shi, Ke Li

Proc. ASME. IMECE2021, Volume 12: Mechanics of Solids, Structures, and Fluids; Micro- and Nano- Systems Engineering and Packaging, V012T12A057, November 1–5, 2021

Paper No: IMECE2021-72222

DOI: https://doi.org/10.1115/IMECE2021-72222

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Topics: Collapse, Finite element analysis, Machine learning, Stress, Wireline equipment

Proceedings Papers

A Bayesian Machine Learning Framework for Selection of the Strain Gradient Plasticity Multiscale Model

Jingye Tan, Kathryn Maupin, Shuai Shao, Danial Faghihi

Proc. ASME. IMECE2021, Volume 12: Mechanics of Solids, Structures, and Fluids; Micro- and Nano- Systems Engineering and Packaging, V012T12A009, November 1–5, 2021

Paper No: IMECE2021-69693

DOI: https://doi.org/10.1115/IMECE2021-69693

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Topics: Machine learning, Plasticity, Strain gradient, Deformation, Dislocations, Engineering simulation, Simulation, Size effect, Uncertainty, Chaos

Proceedings Papers

A Review of SQL vs NoSQL Database for Nuclear Reactor Digital Twin Applications: With Example MongoDB Based NoSQL Database for Digital Twin Model of a Pressurized-Water-Reactor Steam-Generator

Subhasish Mohanty, Thomas W. Elmer, Sasan Bakhtiari, Richard B. Vilim

Proc. ASME. IMECE2021, Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters, V013T14A003, November 1–5, 2021

Paper No: IMECE2021-73153

DOI: https://doi.org/10.1115/IMECE2021-73153

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Topics: Boilers, Databases, Nuclear reactors, Pressurized water reactors, Relational databases, Artificial intelligence, Eddies (Fluid dynamics), Eddy currents (Electricity), Heat transfer, Machine learning

Proceedings Papers

An Overview of the Research Landscape in the Field of Safe Machine Learning

Georg Siedel, Stefan Voß, Silvia Vock

Proc. ASME. IMECE2021, Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters, V013T14A045, November 1–5, 2021

Paper No: IMECE2021-69390

DOI: https://doi.org/10.1115/IMECE2021-69390

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Topics: Machine learning, Safety, Visualization

Proceedings Papers

Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information

Alice Agogino, Hae Young Jang, Vivek Rao, Ritik Batra, Felicity Liao, Rohan Sood, Irving Fang, R. Lily Hu, Emerson Shoichet-Bartus, John Matranga

Proc. ASME. IMECE2021, Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters, V013T14A027, November 1–5, 2021

Paper No: IMECE2021-70759

DOI: https://doi.org/10.1115/IMECE2021-70759

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Topics: Machine learning, Robots, Sensors, Emergencies, Emergency response, Artificial neural networks, Decision making, Density, Disasters, Errors

Proceedings Papers

Anomaly Detection for Cyber-Physical Systems Using Transformers

Yuliang Ma, Andrey Morozov, Sheng Ding

Proc. ASME. IMECE2021, Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters, V013T14A038, November 1–5, 2021

Paper No: IMECE2021-69395

DOI: https://doi.org/10.1115/IMECE2021-69395

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Topics: Cyber-physical systems, Machine learning, Robots, Time series, Artificial neural networks, Economics , Errors, Failure, Hazards, Natural language processing

Proceedings Papers

Solar Distillation Systems Enriched With Machine Learning Techniques: A Review

Y. S. Prasanna, Sandip S. Deshmukh

Proc. ASME. IMECE2021, Volume 8B: Energy, V08BT08A031, November 1–5, 2021

Paper No: IMECE2021-71174

DOI: https://doi.org/10.1115/IMECE2021-71174

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Topics: Machine learning, Solar stills

Proceedings Papers

Deriving Thermal Model From Data by Sparse Identification Based on Physical Laws

Tomoyuki Suzuki, Akira Kano, Kenji Hirohata

Proc. ASME. IMECE2021, Volume 11: Heat Transfer and Thermal Engineering, V011T11A003, November 1–5, 2021

Paper No: IMECE2021-70639

DOI: https://doi.org/10.1115/IMECE2021-70639

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Topics: Design, Forced convection, Heat capacity, Heat transfer, Machine learning, Maintenance, Natural convection, Network models, Nonlinear dynamical systems, Physical laws

Proceedings Papers

Parametric Analysis and Validation of Machine Learning in Chaotic Transitions of the Lorenz System

Ben Tribelhorn, H. E. Dillon

Proc. ASME. IMECE2021, Volume 11: Heat Transfer and Thermal Engineering, V011T11A026, November 1–5, 2021

Paper No: IMECE2021-71766

DOI: https://doi.org/10.1115/IMECE2021-71766

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Topics: Machine learning, Natural convection, Spectral energy distribution, Algorithms, Convection, Dimensions, Flow (Dynamics), Geometry, Heat transfer, Numerical analysis

Proceedings Papers

Communications and Learning for DevOps (CALDO): A Framework for Leveraging Automation for Human Performance Support and Training Systems

E. J. LeBlanc

Proc. ASME. IMECE2021, Volume 6: Design, Systems, and Complexity, V006T06A023, November 1–5, 2021

Paper No: IMECE2021-69428

DOI: https://doi.org/10.1115/IMECE2021-69428

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Topics: Machine learning, Manufacturing, Software development

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NARROW

A New Approach to Develop an Intelligent Robotic Gripper Using Virtual Tools Implementing IIoT and ML Technologies

A New Approach to Develop an Intelligent Manufacturing System Using Virtual Tools

A Machine Learning Approach for Predicting Melt-Pool Dynamics of Ti-6Al-4V Alloy in the Laser Powder-Bed Fusion Process

Ultrasonic Characterization of Biomimetic Porous Scaffold Using Machine Learning: Application of Biot’s Theory

Study on Underwater Friction Stir Welded AA 2024-T3 Pipes Using Machine Learning Algorithms

Digital Twin: Universal User Interface for Online Management of the Manufacturing System

Intelligent Process Control Following Industry 4.0 Trends

Application of Data Processing and Machine Learning Techniques for In Situ Monitoring of Metal Additive Manufacturing Using Acoustic Emission Data

Deformation Manifold Learning Model for Deformation of Multi-Walled Carbon Nano-Tubes: Exploring the Latent Space

Applied Machine Learning Method to Predict Crack Propagation Path in Polycrystalline Graphene Sheet

A Nonlinear Finite Element-Based Supervised Machine Learning Approach for Efficiently Predicting Collapse Resistance of Wireline Tool Housings Subjected to Combined Loads

A Bayesian Machine Learning Framework for Selection of the Strain Gradient Plasticity Multiscale Model

A Review of SQL vs NoSQL Database for Nuclear Reactor Digital Twin Applications: With Example MongoDB Based NoSQL Database for Digital Twin Model of a Pressurized-Water-Reactor Steam-Generator

An Overview of the Research Landscape in the Field of Safe Machine Learning

Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information

Anomaly Detection for Cyber-Physical Systems Using Transformers

Solar Distillation Systems Enriched With Machine Learning Techniques: A Review

Deriving Thermal Model From Data by Sparse Identification Based on Physical Laws

Parametric Analysis and Validation of Machine Learning in Chaotic Transitions of the Lorenz System

Communications and Learning for DevOps (CALDO): A Framework for Leveraging Automation for Human Performance Support and Training Systems

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