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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
https://doi.org/10.1115/ICEF2022-89295
View Paper titled, Using Machine Learning to Predict Derived Cetane Number and Fuel Similarity
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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
https://doi.org/10.1115/ICEF2022-89893
View Paper titled, Deep Learning for Surface Assessment of Cylinder Liners in Large Internal Combustion Engines
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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
https://doi.org/10.1115/ICEF2022-91016
View Paper titled, Predicting Combustion Variability Using Machine Learning From the Flow Field Data at Spark Timing for a Gasoline Direct Injection Engine
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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
https://doi.org/10.1115/ICEF2022-91169
View Paper titled, Machine Learning and Genetic Algorithm Method for Powertrain Development: Rapid Generation of Engine Calibration Maps
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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
https://doi.org/10.1115/ICEF2021-67594
View Paper titled, A Machine Learning Based Numerical Approach for Valve Seating Velocity Control in an Electromagnetic Camless System
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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
https://doi.org/10.1115/ICEF2021-67925
View Paper titled, Data-Driven Approaches to Learn HyChem Models
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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
https://doi.org/10.1115/ICEF2021-67888
View Paper titled, Machine Learning-Enabled Prediction of Transient Injection Map In Automotive Injectors With Uncertainty Quantification
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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
https://doi.org/10.1115/ICEF2020-2968
View Paper titled, Improving Machine Learning Model Performance in Predicting the Indicated Mean Effective Pressure of a Natural Gas Engine
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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
https://doi.org/10.1115/ICEF2020-3000
View Paper titled, An Automated Machine Learning-Genetic Algorithm (AutoML-GA) Framework With Active Learning for Design Optimization
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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
https://doi.org/10.1115/ICEF2019-7237
View Paper titled, A Novel Active Optimization Approach for Rapid and Efficient Design Space Exploration Using Ensemble Machine Learning
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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
https://doi.org/10.1115/ICEF2019-7238
View Paper titled, Engine Combustion System Optimization Using CFD and Machine Learning: A Methodological Approach
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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
https://doi.org/10.1115/ICEF2019-7120
View Paper titled, Diesel Engine Acoustic Diagnostics With Machine Learning During Various Degradation Modes
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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
https://doi.org/10.1115/ICEF2018-9726
View Paper titled, Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators
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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
https://doi.org/10.1115/ICEF2018-9601
View Paper titled, Diesel Engine Acoustic Emission Airflow Clogging Diagnostics With Machine Learning
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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
https://doi.org/10.1115/ICEF2017-3604
View Paper titled, Machine Learning Analysis of Factors Impacting Cycle-to-Cycle Variation in a Gasoline Spark-Ignited Engine
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Topics: Cycles, Engines, Gasoline, Machine learning, Cylinders, Flames, Flow (Dynamics), Ignition, Pressure, Topology