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Journal Articles

A Novel Data Assimilation-Based Real-Time State Estimation Method for Gas Influx Profiling During Riser Gas Events

Chen Wei, Jagadeeshwar L. Tabjula, Jyotsna Sharma, Yuanhang Chen

J. Energy Resour. Technol. September 2023, 145(9): 092901.

Paper No: JERT-22-1800

DOI: https://doi.org/10.1115/1.4056724

Published Online: March 13, 2023

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Topics: Inflow, Kalman filters, Pipeline risers, Pressure, Risers (Casting), State estimation, Porosity, Errors, Uncertainty, Pumps

Journal Articles

A Semi-Analytical Approach for Calculating Productivity Index in Vertical Flowing Well: High Gas-Oil Ratio Field Data as a Case Study

Adesina Fadairo, Kegang Ling, Vamegh Rasouli, Gbadegesin Adeyemi

J. Energy Resour. Technol. November 2022, 144(11): 113006.

Paper No: JERT-21-1868

DOI: https://doi.org/10.1115/1.4054421

Published Online: May 16, 2022

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Topics: Flow (Dynamics), Pipes, Pressure, Wells, Water, Fluids, Steady state, Errors, Reliability, Petroleum

Journal Articles

Prediction of Short-Term Photovoltaic Power Via Self-Attention-Based Deep Learning Approach

Jie Li, Huimeng Niu, Fanxi Meng, Runran Li

J. Energy Resour. Technol. October 2022, 144(10): 101301.

Paper No: JERT-21-1815

DOI: https://doi.org/10.1115/1.4053738

Published Online: March 2, 2022

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Topics: Algorithms, Artificial neural networks, Errors, Weight (Mass), Energy generation, Resolution (Optics), Power grids, Solar cell arrays, Stability

Journal Articles

Localization of Thermal Wellbore Defects Using Machine Learning

Kathryn Bruss, Raymond Kim, Taylor A. Myers, Jiann-Cherng Su, Anirban Mazumdar

J. Energy Resour. Technol. September 2022, 144(9): 093005.

Paper No: JERT-21-1256

DOI: https://doi.org/10.1115/1.4053516

Published Online: February 16, 2022

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Topics: Algorithms, Machine learning, Sensors, Simulation, Temperature, Errors, Geothermal engineering, Artificial neural networks

Journal Articles

Genetic Optimization for Engine Combustion System Calibration: A Case Study of Optimization Performance Sensitivity to Algorithm Search Parameters

Andrew B. Mansfield, Varun Chakrapani, Qingyu Li, Margaret S. Wooldridge

J. Energy Resour. Technol. August 2022, 144(8): 082308.

Paper No: JERT-21-1742

DOI: https://doi.org/10.1115/1.4053347

Published Online: January 21, 2022

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Topics: Algorithms, Calibration, Combustion systems, Engines, Nitrogen oxides, Optimization, Optimization algorithms, Errors

Journal Articles

Comparison of Random Forest and Neural Network in Modeling the Performance and Emissions of a Natural Gas Spark Ignition Engine

Jinlong Liu, Qiao Huang, Christopher Ulishney, Cosmin E. Dumitrescu

J. Energy Resour. Technol. March 2022, 144(3): 032310.

Paper No: JERT-21-1797

DOI: https://doi.org/10.1115/1.4053301

Published Online: January 7, 2022

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Topics: Artificial neural networks, Emissions, Engines, Errors, Machine learning, Natural gas, Algorithms, Combustion, Modeling, Cylinders

Journal Articles

Economic Control for a Residential Photovoltaic-Battery System by Combining Stochastic Model Predictive Control and Improved Correction Strategy

Xinchen Deng, Zhongwei Deng, Ziyou Song, Xianke Lin, Xiaosong Hu

J. Energy Resour. Technol. May 2022, 144(5): 054501.

Paper No: JERT-21-1201

DOI: https://doi.org/10.1115/1.4051735

Published Online: July 30, 2021

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Topics: Batteries, Economics , Flow (Dynamics), Predictive control, Uncertainty, Errors, Energy storage, Stress, Power grids, Energy generation

Journal Articles

Machine Learning Integration With Combustion Physics to Develop a Composite Predictive Model for Reactivity Controlled Compression Ignition Engine

Chinmaya Mishra, P. M. V. Subbarao

J. Energy Resour. Technol. April 2022, 144(4): 042302.

Paper No: JERT-21-1196

DOI: https://doi.org/10.1115/1.4051570

Published Online: July 15, 2021

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Topics: Combustion, Composite materials, Engines, Machine learning, Physics, Pressure, Errors, Cycles, Fuels

Journal Articles

A Data-Driven Machine Learning Approach to Predict the Natural Gas Density of Pure and Mixed Hydrocarbons

Zeeshan Tariq, Amjed Hassan, Umair Bin Waheed, Mohamed Mahmoud, Dhafer Al-Shehri, Abdulazeez Abdulraheem, Esmail M. A. Mokheimer

J. Energy Resour. Technol. September 2021, 143(9): 092801.

Paper No: JERT-21-1396

DOI: https://doi.org/10.1115/1.4051259

Published Online: June 9, 2021

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Topics: Artificial neural networks, Density, Machine learning, Natural gas, Pressure, Errors, Temperature, Modeling, Molecular weight

Journal Articles

Leveraging Machine Learning (Artificial Neural Networks) for Enhancing Performance and Reliability of Thermal Energy Storage Platforms Utilizing Phase Change Materials

Aditya Chuttar, Ashok Thyagarajan, Debjyoti Banerjee

J. Energy Resour. Technol. February 2022, 144(2): 022001.

Paper No: JERT-21-1205

DOI: https://doi.org/10.1115/1.4051048

Published Online: May 31, 2021

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Topics: Artificial neural networks, Reliability, Phase change materials, Temperature, Thermal energy storage, Machine learning, Errors

Journal Articles

Accurate Boundary Layer Measurements Using Hot-Wire Anemometry—Improvements and Error Analysis

Silvio Chemnitz, Reinhard Niehuis

J. Energy Resour. Technol. January 2022, 144(1): 012110.

Paper No: JERT-20-2110

DOI: https://doi.org/10.1115/1.4051095

Published Online: May 27, 2021

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Topics: Boundary layers, Errors, Heat, Uncertainty, Wire, Probes, Sensors, Error analysis

Journal Articles

Prediction of Calorific Value of Coal by Multilinear Regression and Analysis of Variance

M. Sözer, H. Haykiri-Acma, S. Yaman

J. Energy Resour. Technol. January 2022, 144(1): 012103.

Paper No: JERT-20-1900

DOI: https://doi.org/10.1115/1.4050880

Published Online: May 13, 2021

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Topics: Coal, Errors, Heating

Journal Articles

Experimental Study on a New Small-Scale Absorption System: Response Surface and Inverse Analyses

Gaurav Singh, Ranjan Das

J. Energy Resour. Technol. September 2021, 143(9): 092103.

Paper No: JERT-20-2040

DOI: https://doi.org/10.1115/1.4050782

Published Online: May 3, 2021

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Topics: Absorption, Condensers (steam plant), Generators, Heat transfer coefficients, Response surface methodology, Temperature, Water, Heat, Design, Hot water

Journal Articles

Rock Strength Prediction in Real-Time While Drilling Employing Random Forest and Functional Network Techniques

Hany Gamal, Ahmed Alsaihati, Salaheldin Elkatatny, Saleh Haidary, Abdulazeez Abdulraheem

J. Energy Resour. Technol. September 2021, 143(9): 093004.

Paper No: JERT-20-1898

DOI: https://doi.org/10.1115/1.4050843

Published Online: May 3, 2021

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Topics: Artificial intelligence, Drilling, Principal component analysis, Rocks, Testing, Errors, Reservoirs, Compressive strength, Petroleum industry

Journal Articles

Machine Learning-Based Improved Pressure–Volume–Temperature Correlations for Black Oil Reservoirs

Zeeshan Tariq, Mohamed Mahmoud, Abdulazeez Abdulraheem

J. Energy Resour. Technol. November 2021, 143(11): 113003.

Paper No: JERT-21-1031

DOI: https://doi.org/10.1115/1.4050579

Published Online: April 19, 2021

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Topics: Algorithms, Artificial neural networks, Hydrocarbon reservoirs, Machine learning, Machinery, Modeling, Particle swarm optimization, Petroleum engineering, Pressure, Reservoirs

Journal Articles

An Automated Machine Learning-Genetic Algorithm Framework With Active Learning for Design Optimization

Opeoluwa Owoyele, Pinaki Pal, Alvaro Vidal Torreira

J. Energy Resour. Technol. August 2021, 143(8): 082305.

Paper No: JERT-21-1175

DOI: https://doi.org/10.1115/1.4050489

Published Online: April 9, 2021

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Topics: Algorithms, Design, Errors, Machinery, Optimization, Computational fluid dynamics, Simulation, Engines

Journal Articles

Experimental Evaluation of Volatile Organic Compound Quantification Methods for Reciprocating Natural Gas Engines

Brenna King, Mukund Venkitachalam, Daniel Olsen

J. Energy Resour. Technol. July 2021, 143(7): 072303.

Paper No: JERT-20-2102

DOI: https://doi.org/10.1115/1.4050005

Published Online: February 26, 2021

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Topics: Emissions, Engines, Exhaust systems, Flames, Fourier transform infrared spectroscopy, Fuels, Gas engines, Methane, Organic compounds, Sensors

Journal Articles

Analysis and Modeling of Liquid Holdup in Low Liquid Loading Two-Phase Flow Using Computational Fluid Dynamics and Experimental Data

Miguel Ballesteros, Nicolás Ratkovich, Eduardo Pereyra

J. Energy Resour. Technol. January 2021, 143(1): 012105.

Paper No: JERT-19-1553

DOI: https://doi.org/10.1115/1.4047604

Published Online: August 3, 2020

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Topics: Computational fluid dynamics, Flow (Dynamics), Fluids, Modeling, Physics, Pipelines, Pipes, Simulation, Errors, Condensed matter

Journal Articles

Improved Method for the Estimation of Minimum Miscibility Pressure for Pure and Impure CO 2 –Crude Oil Systems Using Gaussian Process Machine Learning Approach

Gerald Kelechi Ekechukwu, Olugbenga Falode, Oyinkepreye David Orodu

J. Energy Resour. Technol. December 2020, 142(12): 123003.

Paper No: JERT-19-1692

DOI: https://doi.org/10.1115/1.4047322

Published Online: June 12, 2020

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Topics: Carbon dioxide, Errors, Machine learning, Pressure, Crude oil, Tertiary petroleum recovery

Journal Articles

A Forecasting Method of District Heat Load Based on Improved Wavelet Neural Network

Zhongbin Zhang, Ye Liu, Lihua Cao, Heyong Si

J. Energy Resour. Technol. October 2020, 142(10): 102102.

Paper No: JERT-20-1009

DOI: https://doi.org/10.1115/1.4047020

Published Online: May 21, 2020

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Topics: Artificial neural networks, Central heating, Errors, Genetic algorithms, Heat, Stress, Wavelets

2 3 4

Journal citation

NARROW

A Novel Data Assimilation-Based Real-Time State Estimation Method for Gas Influx Profiling During Riser Gas Events

A Semi-Analytical Approach for Calculating Productivity Index in Vertical Flowing Well: High Gas-Oil Ratio Field Data as a Case Study

Prediction of Short-Term Photovoltaic Power Via Self-Attention-Based Deep Learning Approach

Localization of Thermal Wellbore Defects Using Machine Learning

Genetic Optimization for Engine Combustion System Calibration: A Case Study of Optimization Performance Sensitivity to Algorithm Search Parameters

Comparison of Random Forest and Neural Network in Modeling the Performance and Emissions of a Natural Gas Spark Ignition Engine

Economic Control for a Residential Photovoltaic-Battery System by Combining Stochastic Model Predictive Control and Improved Correction Strategy

Machine Learning Integration With Combustion Physics to Develop a Composite Predictive Model for Reactivity Controlled Compression Ignition Engine

A Data-Driven Machine Learning Approach to Predict the Natural Gas Density of Pure and Mixed Hydrocarbons

Leveraging Machine Learning (Artificial Neural Networks) for Enhancing Performance and Reliability of Thermal Energy Storage Platforms Utilizing Phase Change Materials

Accurate Boundary Layer Measurements Using Hot-Wire Anemometry—Improvements and Error Analysis

Prediction of Calorific Value of Coal by Multilinear Regression and Analysis of Variance

Experimental Study on a New Small-Scale Absorption System: Response Surface and Inverse Analyses

Rock Strength Prediction in Real-Time While Drilling Employing Random Forest and Functional Network Techniques

Machine Learning-Based Improved Pressure–Volume–Temperature Correlations for Black Oil Reservoirs

An Automated Machine Learning-Genetic Algorithm Framework With Active Learning for Design Optimization

Experimental Evaluation of Volatile Organic Compound Quantification Methods for Reciprocating Natural Gas Engines

Analysis and Modeling of Liquid Holdup in Low Liquid Loading Two-Phase Flow Using Computational Fluid Dynamics and Experimental Data

Improved Method for the Estimation of Minimum Miscibility Pressure for Pure and Impure CO 2 –Crude Oil Systems Using Gaussian Process Machine Learning Approach

A Forecasting Method of District Heat Load Based on Improved Wavelet Neural Network

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