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Proceedings Papers

Using Machine Learning to Predict Derived Cetane Number and Fuel Similarity

Jim Cowart, Terrence Dickerson, Andy McDaniel, Dianne Luning Prak

Proc. ASME. ICEF2022, ASME 2022 ICE Forward Conference, V001T02A004, October 16–19, 2022

Paper No: ICEF2022-89295

DOI: https://doi.org/10.1115/ICEF2022-89295

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Topics: Fuels, Machine learning

Proceedings Papers

Deep Learning for Surface Assessment of Cylinder Liners in Large Internal Combustion Engines

Matthias Schwab, Adéla Moravová, Christoph Angermann, Steinbjörn Jónsson, Christian Laubichler, Constantin Kiesling, Markus Haltmeier

Proc. ASME. ICEF2022, ASME 2022 ICE Forward Conference, V001T01A004, October 16–19, 2022

Paper No: ICEF2022-89893

DOI: https://doi.org/10.1115/ICEF2022-89893

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Topics: Artificial neural networks, Cylinders, Engines, Internal combustion engines, Wear, Reflection, Resolution (Optics), Automotive industry, Condition monitoring, Damage

Proceedings Papers

Predicting Combustion Variability Using Machine Learning From the Flow Field Data at Spark Timing for a Gasoline Direct Injection Engine

Daniel Probst, Nitesh Attal, Raju Mandhapati, Oshin Avanessian

Proc. ASME. ICEF2022, ASME 2022 ICE Forward Conference, V001T06A009, October 16–19, 2022

Paper No: ICEF2022-91016

DOI: https://doi.org/10.1115/ICEF2022-91016

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Topics: Combustion, Direct injection spark ignition engines, Flow (Dynamics), Machine learning, Cycles, Simulation, Pressure, Computational fluid dynamics, Cylinders, Exhaust systems

Proceedings Papers

Machine Learning and Genetic Algorithm Method for Powertrain Development: Rapid Generation of Engine Calibration Maps

Zachary L. Williams, Prathik Meruva, Daniel Christopher Bitsis, Jr.

Proc. ASME. ICEF2022, ASME 2022 ICE Forward Conference, V001T04A006, October 16–19, 2022

Paper No: ICEF2022-91169

DOI: https://doi.org/10.1115/ICEF2022-91169

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Topics: Artificial neural networks, Calibration, Engines, Genetic algorithms, Machine learning

Proceedings Papers

A Machine Learning Based Numerical Approach for Valve Seating Velocity Control in an Electromagnetic Camless System

Srinibas Tripathy, Mithun Babu M., Kanupriya M., Mayank Mittal

Proc. ASME. ICEF2021, ASME 2021 Internal Combustion Engine Division Fall Technical Conference, V001T02A002, October 13–15, 2021

Paper No: ICEF2021-67594

DOI: https://doi.org/10.1115/ICEF2021-67594

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Topics: Control systems, Machine learning, Valves

Proceedings Papers

Data-Driven Approaches to Learn HyChem Models

Weiqi Ji, Julian Zanders, Ji-Woong Park, Sili Deng

Proc. ASME. ICEF2021, ASME 2021 Internal Combustion Engine Division Fall Technical Conference, V001T06A011, October 13–15, 2021

Paper No: ICEF2021-67925

DOI: https://doi.org/10.1115/ICEF2021-67925

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Topics: Chemistry, Combustion, Engineering simulation, Fuels, Genetic algorithms, High temperature, Ignition delay, Internal combustion engines, Low temperature, Machine learning

Proceedings Papers

Machine Learning-Enabled Prediction of Transient Injection Map In Automotive Injectors With Uncertainty Quantification

Sudeepta Mondal, Gina M. Magnotti, Bethany Lusch, Romit Maulik, Roberto Torelli

Proc. ASME. ICEF2021, ASME 2021 Internal Combustion Engine Division Fall Technical Conference, V001T03A005, October 13–15, 2021

Paper No: ICEF2021-67888

DOI: https://doi.org/10.1115/ICEF2021-67888

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Topics: Ejectors, Machine learning, Machinery, Transients (Dynamics), Uncertainty quantification

Proceedings Papers

Improving Machine Learning Model Performance in Predicting the Indicated Mean Effective Pressure of a Natural Gas Engine

Jinlong Liu, Christopher Ulishney, Cosmin E. Dumitrescu

Proc. ASME. ICEF2020, ASME 2020 Internal Combustion Engine Division Fall Technical Conference, V001T03A009, November 4–6, 2020

Paper No: ICEF2020-2968

DOI: https://doi.org/10.1115/ICEF2020-2968

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Topics: Gas engines, Machine learning, Pressure, Engines, Algorithms, Boundary-value problems, Combustion, Cylinders, Diesel, Diesel engines

Proceedings Papers

An Automated Machine Learning-Genetic Algorithm (AutoML-GA) Framework With Active Learning for Design Optimization

Opeoluwa Owoyele, Pinaki Pal, Alvaro Vidal Torreira

Proc. ASME. ICEF2020, ASME 2020 Internal Combustion Engine Division Fall Technical Conference, V001T06A014, November 4–6, 2020

Paper No: ICEF2020-3000

DOI: https://doi.org/10.1115/ICEF2020-3000

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Topics: Algorithms, Design, Machinery, Optimization, Simulation, Computational fluid dynamics, Internal combustion engines, Cylinders, Diesel engines, Errors

Proceedings Papers

A Novel Active Optimization Approach for Rapid and Efficient Design Space Exploration Using Ensemble Machine Learning

Opeoluwa Owoyele, Pinaki Pal

Proc. ASME. ICEF2019, ASME 2019 Internal Combustion Engine Division Fall Technical Conference, V001T06A006, October 20–23, 2019

Paper No: ICEF2019-7237

DOI: https://doi.org/10.1115/ICEF2019-7237

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Topics: Design, Machine learning, Optimization, Algorithms, Combustion, Particle swarm optimization, Cylinders, Engines, Flow (Dynamics), Fuels

Proceedings Papers

Engine Combustion System Optimization Using CFD and Machine Learning: A Methodological Approach

Jihad Badra, Fethi Khaled, Meng Tang, Yuanjiang Pei, Janardhan Kodavasal, Pinaki Pal, Opeoluwa Owoyele, Carsten Fuetterer, Mattia Brenner, Aamir Farooq

Proc. ASME. ICEF2019, ASME 2019 Internal Combustion Engine Division Fall Technical Conference, V001T06A007, October 20–23, 2019

Paper No: ICEF2019-7238

DOI: https://doi.org/10.1115/ICEF2019-7238

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Topics: Combustion systems, Computational fluid dynamics, Engines, Machine learning, Optimization, Pistons

Proceedings Papers

Diesel Engine Acoustic Diagnostics With Machine Learning During Various Degradation Modes

Patrick Moore, Dianne Luning Prak, Len Hamilton, Jim Cowart

Proc. ASME. ICEF2019, ASME 2019 Internal Combustion Engine Division Fall Technical Conference, V001T05A001, October 20–23, 2019

Paper No: ICEF2019-7120

DOI: https://doi.org/10.1115/ICEF2019-7120

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Topics: Acoustics, Diesel engines, Machine learning, Engines, Combustion, Cylinders, Acoustic emissions, Air filters, Artificial neural networks, Errors

Proceedings Papers

Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

Daniel M. Probst, Mandhapati Raju, Peter K. Senecal, Janardhan Kodavasal, Pinaki Pal, Sibendu Som, Ahmed A. Moiz, Yuanjiang Pei

Proc. ASME. ICEF2018, Volume 2: Emissions Control Systems; Instrumentation, Controls, and Hybrids; Numerical Simulation; Engine Design and Mechanical Development, V002T06A023, November 4–7, 2018

Paper No: ICEF2018-9726

DOI: https://doi.org/10.1115/ICEF2018-9726

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Topics: Engineering simulation, Engines, Machine learning, Optimization, Simulation, Computational fluid dynamics, Algorithms, Clocks, Optimization algorithms, Particle swarm optimization

Proceedings Papers

Diesel Engine Acoustic Emission Airflow Clogging Diagnostics With Machine Learning

Jim Cowart, Patrick Moore, Harrison Yosten, Leonard Hamilton, Dianne Luning Prak

Proc. ASME. ICEF2018, Volume 2: Emissions Control Systems; Instrumentation, Controls, and Hybrids; Numerical Simulation; Engine Design and Mechanical Development, V002T05A008, November 4–7, 2018

Paper No: ICEF2018-9601

DOI: https://doi.org/10.1115/ICEF2018-9601

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Topics: Acoustic emissions, Air flow, Diesel engines, Machine learning, Engines, Combustion, Acoustics, Cylinders, Air filters, Artificial neural networks

Proceedings Papers

Machine Learning Analysis of Factors Impacting Cycle-to-Cycle Variation in a Gasoline Spark-Ignited Engine

Janardhan Kodavasal, Ahmed Abdul Moiz, Muhsin Ameen, Sibendu Som

Proc. ASME. ICEF2017, Volume 2: Emissions Control Systems; Instrumentation, Controls, and Hybrids; Numerical Simulation; Engine Design and Mechanical Development, V002T06A020, October 15–18, 2017

Paper No: ICEF2017-3604

DOI: https://doi.org/10.1115/ICEF2017-3604

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Topics: Cycles, Engines, Gasoline, Machine learning, Cylinders, Flames, Flow (Dynamics), Ignition, Pressure, Topology

NARROW

Using Machine Learning to Predict Derived Cetane Number and Fuel Similarity

Deep Learning for Surface Assessment of Cylinder Liners in Large Internal Combustion Engines

Predicting Combustion Variability Using Machine Learning From the Flow Field Data at Spark Timing for a Gasoline Direct Injection Engine

Machine Learning and Genetic Algorithm Method for Powertrain Development: Rapid Generation of Engine Calibration Maps

A Machine Learning Based Numerical Approach for Valve Seating Velocity Control in an Electromagnetic Camless System

Data-Driven Approaches to Learn HyChem Models

Machine Learning-Enabled Prediction of Transient Injection Map In Automotive Injectors With Uncertainty Quantification

Improving Machine Learning Model Performance in Predicting the Indicated Mean Effective Pressure of a Natural Gas Engine

An Automated Machine Learning-Genetic Algorithm (AutoML-GA) Framework With Active Learning for Design Optimization

A Novel Active Optimization Approach for Rapid and Efficient Design Space Exploration Using Ensemble Machine Learning

Engine Combustion System Optimization Using CFD and Machine Learning: A Methodological Approach

Diesel Engine Acoustic Diagnostics With Machine Learning During Various Degradation Modes

Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

Diesel Engine Acoustic Emission Airflow Clogging Diagnostics With Machine Learning

Machine Learning Analysis of Factors Impacting Cycle-to-Cycle Variation in a Gasoline Spark-Ignited Engine

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