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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

Accelerating Chemical Kinetics Calculations With Physics Informed Neural Networks

Ahmed Almeldein, Noah Van Dam
Proc. ASME. ICEF2022, ASME 2022 ICE Forward Conference, V001T06A007, October 16–19, 2022
Paper No: ICEF2022-90371
https://doi.org/10.1115/ICEF2022-90371
View Paper titled, Accelerating Chemical Kinetics Calculations With Physics Informed Neural Networks
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Topics: Artificial neural networks, Chemical kinetics, Physics, Combustion, Engineering simulation, Modeling, Physical laws, Simulation, Architecture, Chemistry
Proceedings Papers

Predicting the Cetane Number, Sooting Tendency, and Energy Density of Terpene Fuel Additives

Travis Kessler, Amina SubLaban, J. Hunter Mack
Proc. ASME. ICEF2022, ASME 2022 ICE Forward Conference, V001T02A011, October 16–19, 2022
Paper No: ICEF2022-91163
https://doi.org/10.1115/ICEF2022-91163
View Paper titled, Predicting the Cetane Number, Sooting Tendency, and Energy Density of Terpene Fuel Additives
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Topics: Density, Fuels, Carbon, Errors, Artificial neural networks, Chain, Combustion, Emissions, Engines, Heating
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

Evaluating Diesel/Biofuel Blends Using Artificial Neural Networks and Linear/Nonlinear Equations

Travis Kessler, Thomas Schwartz, Hsi-Wu Wong, J. Hunter Mack
Proc. ASME. ICEF2021, ASME 2021 Internal Combustion Engine Division Fall Technical Conference, V001T04A009, October 13–15, 2021
Paper No: ICEF2021-67785
https://doi.org/10.1115/ICEF2021-67785
View Paper titled, Evaluating Diesel/Biofuel Blends Using Artificial Neural Networks and Linear/Nonlinear Equations
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Topics: Artificial neural networks, Biofuel, Diesel, Nonlinear equations, Errors, Heating, Kinematics, Viscosity, Biomass, Combustion
Proceedings Papers

Predicting the Cetane Number, Yield Sooting Index, Kinematic Viscosity, and Cloud Point for Catalytically Upgraded Pyrolysis Oil Using Artificial Neural Networks

Travis Kessler, Thomas Schwartz, Hsi-Wu Wong, J. Hunter Mack
Proc. ASME. ICEF2020, ASME 2020 Internal Combustion Engine Division Fall Technical Conference, V001T02A006, November 4–6, 2020
Paper No: ICEF2020-2978
https://doi.org/10.1115/ICEF2020-2978
View Paper titled, Predicting the Cetane Number, Yield Sooting Index, Kinematic Viscosity, and Cloud Point for Catalytically Upgraded Pyrolysis Oil Using Artificial Neural Networks
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Topics: Artificial neural networks, Kinematics, Pyrolysis, Viscosity, Diesel, Errors, Fuels, Biomass, Fuel gasification, Oxygen
Proceedings Papers

Study on Automatic Adaptation for a Control-Oriented Model of an Advanced Diesel Engine

S. Nishii, Y. Yamasaki
Proc. ASME. ICEF2020, ASME 2020 Internal Combustion Engine Division Fall Technical Conference, V001T04A008, November 4–6, 2020
Paper No: ICEF2020-3025
https://doi.org/10.1115/ICEF2020-3025
View Paper titled, Study on Automatic Adaptation for a Control-Oriented Model of an Advanced Diesel Engine
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Topics: Diesel engines, Artificial neural networks, Combustion, Engines, Algorithms, Combustion technologies, Heat, Ignition, Optimization algorithms, Physics
Proceedings Papers

Prediction of NO x Emissions for a Range of Engine Hardware Configurations Using Artificial Neural Networks

Nick Papaioannou, XiaoHang Fang, Felix Leach, Martin H. Davy
Proc. ASME. ICEF2020, ASME 2020 Internal Combustion Engine Division Fall Technical Conference, V001T06A001, November 4–6, 2020
Paper No: ICEF2020-2911
https://doi.org/10.1115/ICEF2020-2911
View Paper titled, Prediction of NO x Emissions for a Range of Engine Hardware Configurations Using Artificial Neural Networks
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Topics: Artificial neural networks, Emissions, Engines, Hardware, Nitrogen oxides, Diesel engines, Ejectors, Feedforward control, Fuels, Nozzles
Proceedings Papers

Screening Compounds for Fast Pyrolysis and Catalytic Biofuel Upgrading Using Artificial Neural Networks

Travis Kessler, Thomas Schwartz, Hsi-Wu Wong, J. Hunter Mack
Proc. ASME. ICEF2019, ASME 2019 Internal Combustion Engine Division Fall Technical Conference, V001T02A007, October 20–23, 2019
Paper No: ICEF2019-7170
https://doi.org/10.1115/ICEF2019-7170
View Paper titled, Screening Compounds for Fast Pyrolysis and Catalytic Biofuel Upgrading Using Artificial Neural Networks
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Topics: Artificial neural networks, Biofuel, Pyrolysis, Fuels, Diesel engines, Errors, Feedback, Biomass, Combustion, Fuel gasification
Proceedings Papers

Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions

Pinaki Pal, Krishna Kalvakala, Yunchao Wu, Matthew McNenly, Simon Lapointe, Russell Whitesides, Tianfeng Lu, Suresh K. Aggarwal, Sibendu Som
Proc. ASME. ICEF2019, ASME 2019 Internal Combustion Engine Division Fall Technical Conference, V001T02A015, October 20–23, 2019
Paper No: ICEF2019-7284
https://doi.org/10.1115/ICEF2019-7284
View Paper titled, Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions
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Topics: Fuels, Ignition, Flames, Engines, Artificial neural networks, Computational fluid dynamics, Computer simulation, Pressure, Regression models, Temperature
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

Development of an Artificial Neural Network Model for the Performance Prediction of a Variable Compression Ratio Gasoline Spark Ignition Engine

Srinibas Tripathy, Sridhar Sahoo, Dhananjay Kumar Srivastava
Proc. ASME. ICEF2019, ASME 2019 Internal Combustion Engine Division Fall Technical Conference, V001T07A002, October 20–23, 2019
Paper No: ICEF2019-7118
https://doi.org/10.1115/ICEF2019-7118
View Paper titled, Development of an Artificial Neural Network Model for the Performance Prediction of a Variable Compression Ratio Gasoline Spark Ignition Engine
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Topics: Artificial neural networks, Compression, Engines, Gasoline, Spark-ignition engine
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

Application of a Rectified Linear Unit (ReLU) Based Artificial Neural Network to Cetane Number Predictions

Travis Kessler, Gregory Dorian, J. Hunter Mack
Proc. ASME. ICEF2017, Volume 1: Large Bore Engines; Fuels; Advanced Combustion, V001T02A006, October 15–18, 2017
Paper No: ICEF2017-3614
https://doi.org/10.1115/ICEF2017-3614
View Paper titled, Application of a Rectified Linear Unit (ReLU) Based Artificial Neural Network to Cetane Number Predictions
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Topics: Artificial neural networks, Fuels, Errors, Databases, Testing
Proceedings Papers

Control Oriented Modelling of Engine IMEP Variation

Qilun Zhu, Robert Prucka, Shu Wang, Michael Prucka, Hussein Dourra
Proc. ASME. ICEF2016, ASME 2016 Internal Combustion Engine Division Fall Technical Conference, V001T05A001, October 9–12, 2016
Paper No: ICEF2016-9342
https://doi.org/10.1115/ICEF2016-9342
View Paper titled, Control Oriented Modelling of Engine IMEP Variation
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Topics: Engines, Modeling, Combustion, Artificial neural networks, Turbulence, Actuators, Cycles, Cylinders, Engineers, Pressure
Proceedings Papers

Predicting the Cetane Number of Furanic Biofuel Candidates Using an Improved Artificial Neural Network Based on Molecular Structure

Travis Kessler, Eric R. Sacia, Alexis T. Bell, J. Hunter Mack
Proc. ASME. ICEF2016, ASME 2016 Internal Combustion Engine Division Fall Technical Conference, V001T02A010, October 9–12, 2016
Paper No: ICEF2016-9383
https://doi.org/10.1115/ICEF2016-9383
View Paper titled, Predicting the Cetane Number of Furanic Biofuel Candidates Using an Improved Artificial Neural Network Based on Molecular Structure
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Topics: Artificial neural networks, Biofuel, Fuels, Databases, Ignition, Errors, Methane, Testing, ASTM standards, Biomass
Proceedings Papers

Grey-Box Modeling for HCCI Engine Control

M. Bidarvatan, M. Shahbakhti
Proc. ASME. ICEF2013, Volume 1: Large Bore Engines; Advanced Combustion; Emissions Control Systems; Instrumentation, Controls, and Hybrids, V001T05A006, October 13–16, 2013
Paper No: ICEF2013-19097
https://doi.org/10.1115/ICEF2013-19097
View Paper titled, Grey-Box Modeling for HCCI Engine Control
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Topics: Homogeneous charge compression ignition engines, Modeling, Combustion, Artificial neural networks, Computation, Engines, Errors, Exhaust systems, Feedforward control, Pressure
Proceedings Papers

Artificial Neural Network for Predicting Cetane Number of Biofuel Candidates Based on Molecular Structure

T. Sennott, C. Gotianun, R. Serres, M. Ziabasharhagh, J. H. Mack, R. Dibble
Proc. ASME. ICEF2013, Volume 2: Fuels; Numerical Simulation; Engine Design, Lubrication, and Applications, V002T02A009, October 13–16, 2013
Paper No: ICEF2013-19185
https://doi.org/10.1115/ICEF2013-19185
View Paper titled, Artificial Neural Network for Predicting Cetane Number of Biofuel Candidates Based on Molecular Structure
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Topics: Artificial neural networks, Biofuel, Fuels, Diesel, Ethers (Class of compounds), Gasoline, Ignition, Testing
Proceedings Papers

Improved Transient Control of a Two-Stroke Marine Diesel Engine With Variable Geometry Turbine

Nikolaos I. Xiros, Gerasimos Theotokatos
Proc. ASME. ICEF2011, ASME 2011 Internal Combustion Engine Division Fall Technical Conference, 85-94, October 2–5, 2011
Paper No: ICEF2011-60199
https://doi.org/10.1115/ICEF2011-60199
View Paper titled, Improved Transient Control of a Two-Stroke Marine Diesel Engine With Variable Geometry Turbine
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Topics: Algebra, Angular momentum, Artificial neural networks, Control equipment, Cycles, Diesel engines, Differential equations, Engines, Geometry, Power stations
Proceedings Papers

Application of Auto-Associative Neural Networks to Transient Fault Detection in an IC Engine

Neil McDowell, Geoff McCullough, Xun Wang, Uwe Kruger, George W. Irwin
Proc. ASME. ICEF2007, ASME 2007 Internal Combustion Engine Division Fall Technical Conference, 555-562, October 14–17, 2007
Paper No: ICEF2007-1728
https://doi.org/10.1115/ICEF2007-1728
View Paper titled, Application of Auto-Associative Neural Networks to Transient Fault Detection in an IC Engine
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Topics: Artificial neural networks, Flaw detection, Internal combustion engines, Transients (Dynamics), Engines, Automotive engines, Automotive industry, Cycles, Emissions, Four-stroke engines