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Proceedings Papers

Enhanced Capabilities Through Automated Machine Learning Characterization of Natural Gas Powered Assets

Christopher A. Perullo, Steven Seachman, David Noble, Jamie Lim, Lea Boche, Woosung Choi

Proc. ASME. POWER2022, ASME 2022 Power Conference, V001T04A003, July 18–19, 2022

Paper No: POWER2022-86449

DOI: https://doi.org/10.1115/POWER2022-86449

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Topics: Algorithms, Artificial neural networks, Chain, Digital twin, Errors, Gas turbines, Hardware, Instrumentation, Machine learning, Natural gas

Proceedings Papers

Analyzing the Operating Parameters of a Compression Ignition Diesel Engine Using Artificial Neural Network

Jyotirmoy Kakati, Shubham M. More, Sukhomay Pal, Ujjwal K. Saha

Proc. ASME. POWER2022, ASME 2022 Power Conference, V001T07A010, July 18–19, 2022

Paper No: POWER2022-86409

DOI: https://doi.org/10.1115/POWER2022-86409

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Topics: Artificial neural networks, Compression, Diesel engines, Ignition

Proceedings Papers

Physics-Informed Deep Learning-Based Modeling of a Novel Elastohydrodynamic Seal for Supercritical CO 2 Turbomachinery

Karthik Reddy Lyathakula, Sevki Cesmeci, Matthew DeMond, Hanping Xu, Jing Tang

Proc. ASME. POWER2022, ASME 2022 Power Conference, V001T15A008, July 18–19, 2022

Paper No: POWER2022-86597

DOI: https://doi.org/10.1115/POWER2022-86597

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Topics: Artificial neural networks, Modeling, Physics, Supercritical carbon dioxide, Turbomachinery

Proceedings Papers

Classification of Microchannel Flame Regimes Based on Convolutional Neural Networks

Seyed Navid Roohani Isfahani, Vinicius M. Sauer, Ingmar Schoegl

Proc. ASME. POWER2021, ASME 2021 Power Conference, V001T05A005, July 20–22, 2021

Paper No: POWER2021-64437

DOI: https://doi.org/10.1115/POWER2021-64437

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Topics: Artificial neural networks, Flames, Microchannels, Combustion, Fuels, Chemiluminescence, Experimental methods, Filters, Flow (Dynamics), Fossil fuels

Proceedings Papers

Integration of Hydro and Renewable Energy Resources in Energy Planning

Lucero Cynthia Luciano De La Cruz, Cesar Celis

Proc. ASME. POWER2020, ASME 2020 Power Conference, V001T08A008, August 4–5, 2020

Paper No: POWER2020-16376

DOI: https://doi.org/10.1115/POWER2020-16376

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Topics: Renewable energy, Renewable energy sources, Hydropower, Computer software, Artificial neural networks, Biomass, Electric power generation, Energy budget (Physics), Geothermal engineering, Solar energy

Proceedings Papers

A Hybrid Wind Speed Prediction Approach Based on Ensemble Empirical Mode Decomposition and BO-LSTM Neural Networks for Digital Twin

Weifei Hu, Yihan He, Zhenyu Liu, Jianrong Tan, Ming Yang, Jiancheng Chen

Proc. ASME. POWER2020, ASME 2020 Power Conference, V001T08A009, August 4–5, 2020

Paper No: POWER2020-16500

DOI: https://doi.org/10.1115/POWER2020-16500

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Topics: Artificial neural networks, Optimization, Time series, Wind velocity

Proceedings Papers

Building Energy Prediction Using Artificial Neural Networks (LSTM)

Sankhanil Goswami

Proc. ASME. POWER2020, ASME 2020 Power Conference, V001T10A015, August 4–5, 2020

Paper No: POWER2020-16828

DOI: https://doi.org/10.1115/POWER2020-16828

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Topics: Artificial neural networks, Cooling, Energy consumption, Stress

Proceedings Papers

Convolutional Neural Network Model for the Prediction of Plenum Temperature in a Waste Glass Melter

A. W. Abboud, D. P. Guillen, R. Pokorny

Proc. ASME. POWER2020, ASME 2020 Power Conference, V001T11A008, August 4–5, 2020

Paper No: POWER2020-16993

DOI: https://doi.org/10.1115/POWER2020-16993

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Topics: Artificial neural networks, Computational fluid dynamics, Glass, Neural network models, Temperature, Vitrification, Heat transfer, Ceramics, Filters, Fluid dynamics

Proceedings Papers

Using Machine Learning to Increase Model Performance for a Gas Turbine System

Samuel M. Hipple, Zachary T. Reinhart, Harry Bonilla-Alvarado, Paolo Pezzini, Kenneth Mark Bryden

Proc. ASME. POWER2020, ASME 2020 Power Conference, V001T12A003, August 4–5, 2020

Paper No: POWER2020-16580

DOI: https://doi.org/10.1115/POWER2020-16580

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Topics: Artificial neural networks, Gas turbines, Machine learning, Modeling, Turbomachinery

Proceedings Papers

Induced Draft Fan Early Anomaly Identification Based on SIS Data Using Normal Behavior Model in Thermal Power Plant

Di Hu, Sheng Guo, Gang Chen, Cheng Zhang, Dongzhen Lv, Bing Li, Qianming Chen

Proc. ASME. POWER2019, ASME 2019 Power Conference, V001T08A002, July 15–18, 2019

Paper No: POWER2019-1864

DOI: https://doi.org/10.1115/POWER2019-1864

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Topics: Thermal power stations, Condition monitoring, Artificial neural networks, China, Matlab, Power stations

Proceedings Papers

Gas Turbine Engine Price Estimation Using Artificial Neural Network

David Olusina Rowlands, Mark Savill

Proc. ASME. POWER2018, Volume 1: Fuels, Combustion, and Material Handling; Combustion Turbines Combined Cycles; Boilers and Heat Recovery Steam Generators; Virtual Plant and Cyber-Physical Systems; Plant Development and Construction; Renewable Energy Systems, V001T05A001, June 24–28, 2018

Paper No: POWER2018-7141

DOI: https://doi.org/10.1115/POWER2018-7141

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Topics: Artificial neural networks, Gas turbines, Economic analysis, Engines, Performance, Trains

Proceedings Papers

Prediction Model of Flow-Induced Noise in Large-Scale Centrifugal Pumps Based on BP Neural Network

Chang Guo, Ming Gao, Peixin Dong, Yuetao Shi, Fengzhong Sun

Proc. ASME. POWER2017-ICOPE-17, Volume 2: I&C, Digital Controls, and Influence of Human Factors; Plant Construction Issues and Supply Chain Management; Plant Operations, Maintenance, Aging Management, Reliability and Performance; Renewable Energy Systems: Solar, Wind, Hydro and Geothermal; Risk Management, Safety and Cyber Security; Steam Turbine-Generators, Electric Generators, Transformers, Switchgear, and Electric BOP and Auxiliaries; Student Competition; Thermal Hydraulics and Computational Fluid Dynamics, V002T13A006, June 26–30, 2017

Paper No: POWER-ICOPE2017-3280

DOI: https://doi.org/10.1115/POWER-ICOPE2017-3280

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Topics: Artificial neural networks, Centrifugal pumps, Flow (Dynamics), Noise (Sound), Algorithms, Errors, Network models, Neural network models, Pumps, Simulation

Proceedings Papers

Multi-Objective Optimization of Geometrical Parameters of Corrugated-Undulated Heat Transfer Surfaces Using CFD, Artificial Neural Networks and Genetic Algorithms

Limin Wang, Chenglong Ji, Xun Chen, Lei Deng, Yiping Chen, Defu Che

Proc. ASME. POWER2016, ASME 2016 Power Conference, V001T11A010, June 26–30, 2016

Paper No: POWER2016-59489

DOI: https://doi.org/10.1115/POWER2016-59489

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Topics: Artificial neural networks, Computational fluid dynamics, Genetic algorithms, Heat transfer, Pareto optimization, Computer simulation, Finite volume methods, Flow (Dynamics), Fluid dynamics, Friction

Proceedings Papers

Turbulent Flow Energy Budget Calculations in a Dump Combustor Model

Saad Ahmed, Bharath Raghavan, Mohamed Gadalla

Proc. ASME. POWER2014, Volume 1: Fuels and Combustion, Material Handling, Emissions; Steam Generators; Heat Exchangers and Cooling Systems; Turbines, Generators and Auxiliaries; Plant Operations and Maintenance; Reliability, Availability and Maintainability (RAM); Plant Systems, Structures, Components and Materials Issues, V001T01A009, July 28–31, 2014

Paper No: POWER2014-32150

DOI: https://doi.org/10.1115/POWER2014-32150

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Topics: Combustion chambers, Energy budget (Physics), Turbulence, Artificial neural networks, Swirling flow, Flow (Dynamics), Statistics, Feedforward control, Fluid dynamics, Gas turbines

Proceedings Papers

Development of New Instant Technology of Natural Gas Quality Determination

Taras Koturbash, Maksym Karpash, Iryna Darvai, Ihor Rybitskyi, Vladimir Kutcherov

Proc. ASME. POWER2013, Volume 1: Fuels and Combustion, Material Handling, Emissions; Steam Generators; Heat Exchangers and Cooling Systems; Turbines, Generators and Auxiliaries; Plant Operations and Maintenance, V001T01A011, July 29–August 1, 2013

Paper No: POWER2013-98089

DOI: https://doi.org/10.1115/POWER2013-98089

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Topics: Natural gas, Vickers hardness testing, Carbon dioxide, Speed of sound, Artificial neural networks, Databases, Errors, Heating, Instrumentation, Maintenance

Proceedings Papers

Object-Oriented Programming of Turbine Performance Calculation With Cooling Air

Fumin Pan, Hongtao Zheng, Qingzhen Liu

Proc. ASME. POWER2013, Volume 2: Reliability, Availability and Maintainability (RAM); Plant Systems, Structures, Components and Materials Issues; Simple and Combined Cycles; Advanced Energy Systems and Renewables (Wind, Solar and Geothermal); Energy Water Nexus; Thermal Hydraulics and CFD; Nuclear Plant Design, Licensing and Construction; Performance Testing and Performance Test Codes, V002T13A003, July 29–August 1, 2013

Paper No: POWER2013-98191

DOI: https://doi.org/10.1115/POWER2013-98191

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Topics: Computer programming, Cooling, Turbines, Particle swarm optimization, Temperature, Artificial neural networks, Enthalpy, Pressure, Thermodynamic processes

Proceedings Papers

Experiment of Adiabatic Two-Phase Flow in an Annulus Under Low-Frequency Vibration

Shao-Wen Chen, Caleb S. Brooks, Chris Macke, Takashi Hibiki, Mamoru Ishii, Michitsugu Mori

Proc. ASME. ICONE20-POWER2012, Volume 3: Thermal-Hydraulics; Turbines, Generators, and Auxiliaries, 467-476, July 30–August 3, 2012

Paper No: ICONE20-POWER2012-54566

DOI: https://doi.org/10.1115/ICONE20-POWER2012-54566

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Topics: Annulus, Two-phase flow, Vibration, Flow (Dynamics), Porosity, Signals, Artificial neural networks, Boiling water reactors, Displacement, Dynamics (Mechanics)

Proceedings Papers

On the Use of Support Vector Regression Technique for the Analysis of Rod Ejection Accidents

Botao Jiang, Yang Liu, Fuyu Zhao

Proc. ASME. ICONE20-POWER2012, Volume 5: Fusion Engineering; Student Paper Competition; Design Basis and Beyond Design Basis Events; Simple and Combined Cycles, 99-102, July 30–August 3, 2012

Paper No: ICONE20-POWER2012-54266

DOI: https://doi.org/10.1115/ICONE20-POWER2012-54266

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Topics: Accidents, Support vector machines, Artificial neural networks, Pressurized water reactors, Trains, Computers, Design, Machine learning, Nuclear engineering, Power stations

Proceedings Papers

Design Tools for the Performance Improvement of a 76 MW Francis Turbine Runner

Jose´ Manuel Franco-Nava, Oscar Dorantes-Go´mez, Erik Rosado-Tamariz, Jose´ Manuel Ferna´ndez-Da´vila, Reynaldo Rangel-Espinosa

Proc. ASME. POWER2009, ASME 2009 Power Conference, 293-300, July 21–23, 2009

Paper No: POWER2009-81201

DOI: https://doi.org/10.1115/POWER2009-81201

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Topics: Computational fluid dynamics, Design, Francis turbines, Hydraulic turbines, Optimization, Blades, Computation, Finite element analysis, Flow (Dynamics), Fluids

Proceedings Papers

Application of Neural Networks in Fault Diagnosis of Rotating Machinery

Qing He, Dongmei Du

Proc. ASME. POWER2007, ASME 2007 Power Conference, 279-282, July 17–19, 2007

Paper No: POWER2007-22022

DOI: https://doi.org/10.1115/POWER2007-22022

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Topics: Artificial neural networks, Fault diagnosis, Machinery

NARROW

Enhanced Capabilities Through Automated Machine Learning Characterization of Natural Gas Powered Assets

Analyzing the Operating Parameters of a Compression Ignition Diesel Engine Using Artificial Neural Network

Physics-Informed Deep Learning-Based Modeling of a Novel Elastohydrodynamic Seal for Supercritical CO 2 Turbomachinery

Classification of Microchannel Flame Regimes Based on Convolutional Neural Networks

Integration of Hydro and Renewable Energy Resources in Energy Planning

A Hybrid Wind Speed Prediction Approach Based on Ensemble Empirical Mode Decomposition and BO-LSTM Neural Networks for Digital Twin

Building Energy Prediction Using Artificial Neural Networks (LSTM)

Convolutional Neural Network Model for the Prediction of Plenum Temperature in a Waste Glass Melter

Using Machine Learning to Increase Model Performance for a Gas Turbine System

Induced Draft Fan Early Anomaly Identification Based on SIS Data Using Normal Behavior Model in Thermal Power Plant

Gas Turbine Engine Price Estimation Using Artificial Neural Network

Prediction Model of Flow-Induced Noise in Large-Scale Centrifugal Pumps Based on BP Neural Network

Multi-Objective Optimization of Geometrical Parameters of Corrugated-Undulated Heat Transfer Surfaces Using CFD, Artificial Neural Networks and Genetic Algorithms

Turbulent Flow Energy Budget Calculations in a Dump Combustor Model

Development of New Instant Technology of Natural Gas Quality Determination

Object-Oriented Programming of Turbine Performance Calculation With Cooling Air

Experiment of Adiabatic Two-Phase Flow in an Annulus Under Low-Frequency Vibration

On the Use of Support Vector Regression Technique for the Analysis of Rod Ejection Accidents

Design Tools for the Performance Improvement of a 76 MW Francis Turbine Runner

Application of Neural Networks in Fault Diagnosis of Rotating Machinery

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