Article
Computer Science, Artificial Intelligence
Joanna Jedrzejowicz, Piotr Jedrzejowicz
Summary: The paper introduces an incremental Gene Expression Programming classifier for mining imbalanced datasets, which adapts to the requirements of the imbalanced data environment by reusing minority class instances and applying the incremental learning paradigm. Through extensive computational experiments, it demonstrates competitive performance against other state-of-the-art learners in many cases.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Qiang Lu, Congwen Xu, Jake Luo, Zhiguang Wang
Summary: Gene Expression Programming (GEP) is commonly used for symbolic regression (SR) problems, but it often falls into local optima and randomly searches for results, impacting performance. To address these issues, a new algorithm called AB-GEP is proposed, which uses an adversarial bandit (AB) technique to segment the expression space and leverages AvgExp3 for enhanced population jumps between subspaces. Evaluation on benchmark datasets shows that AB-GEP maintains better population diversity and achieves superior results compared to traditional GEP algorithms.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Artificial Intelligence
Joanna Jedrzejowicz, Piotr Jedrzejowicz
Summary: The paper introduces two GEP-based ensemble classifiers with different drift detection mechanisms and validates their effectiveness in experiments.
Article
Engineering, Civil
Muhammad Iftikhar Faraz, Siyab Ul Arifeen, Muhammad Nasir Amin, Afnan Nafees, Fadi Althoey, Akbar Niaz
Summary: Due to the harmful environmental consequences and high cost of cement formation, research focuses on reducing the environmental impact and expense of cement containing products. Understanding the mechanical characteristics of cement additive/replacement products such as metakaolin is crucial, and developing predictive machine learning models is becoming increasingly important as ecological concerns grow. This study examines machine learning methods, such as gene expression programming (GEP) and multigene expression programming (MEP), for forecasting the compressive strength of concrete containing metakaolin. The research findings highlight the effectiveness of MEP as the optimal ML algorithm for predicting the compressive strength of metakaolin-based concrete.
Article
Computer Science, Hardware & Architecture
Lechan Yang, Song Deng, Shouming Ma, Fangxiong Xiao
Summary: This paper proposes an estimation model of leaf nitrogen content based on Gene Expression Programming (GEP) and leaf spectral reflectance. The experimental results show that compared with the other regression algorithms, the model based on GEP has better estimation accuracy, and the selected local band is less affected by moisture.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Geochemistry & Geophysics
Yahui Bu, Qian Sun, Shuoran Fu, Lingkong Guo, Na Zhang
Summary: This paper presents a method for calculating the minimum miscibility pressure (MMP) of pure hydrocarbons and CO2 systems in nanopores. The calculated MMP using this method has a relative error of about 0.62% compared to the traditional method, indicating high reliability. The measured MMP at the nanoscale is generally smaller than that in the bulk phase due to the confinement effect. MMP is positively correlated with reservoir temperature, carbon atom number in alkanes, and nanopore radius.
Article
Biotechnology & Applied Microbiology
Yu Zhong Peng, Yanmei Lin, Yiran Huang, Ying Li, Guangsheng Luo, Jianping Liao
Summary: The study introduces a novel method named GEP-EpiSeeker, based on Gene Expression Programming algorithm, for identifying epistatic interactions in Genome-wide Association Studies. Experimental results demonstrate that GEP-EpiSeeker outperforms comparative methods in detecting epistasis.
Article
Chemistry, Multidisciplinary
Mehdi Mahdaviara, Alireza Rostami, Khalil Shahbazi, Amin Shokrollahi, Mohammad Hossein Ghazanfari
Summary: This paper focuses on developing a new method using Gene Expression Programming (GEP) to estimate the correlation of water-based nanofluids viscosity. The results demonstrate that the proposed method accurately predicts the viscosity of water-based nanofluids.
IRANIAN JOURNAL OF CHEMISTRY & CHEMICAL ENGINEERING-INTERNATIONAL ENGLISH EDITION
(2022)
Article
Engineering, Chemical
Qichao Lv, Rong Zheng, Xinshu Guo, Aydin Larestani, Fahimeh Hadavimoghaddam, Masoud Riazi, Abdolhossein Hemmati-Sarapardeh, Kai Wang, Junjian Li
Summary: The energy demand is increasing globally, while concerns about global warming and greenhouse gases have also grown. Injecting CO2 into mature oil reservoirs is a promising solution to meet the rising demand and address environmental issues. Accurate knowledge of the CO2 minimum miscibility pressure (MMP) is crucial for the successful design of such operations.
SEPARATION AND PURIFICATION TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Jun Zhang, Ruoli Shi, Shaohua Shi, A. K. Alzo'ubi, Angel Roco-Videla, Mohamed M. A. Hussein, Afrasyab Khan
Summary: Analyzing the soil dynamic shear stresses around rectangular tunnel systems is complex due to the interaction of rectangular TBM and the rock, but utilizing algorithms like support vector machine and gene expression programming can enhance the accuracy of predicting these stresses. Support vector machine shows high-performance capacity in predicting soil dynamic shear stresses around the tunnel during rectangular TBM excavation.
ENGINEERING WITH COMPUTERS
(2022)
Article
Automation & Control Systems
Bin Shen, Shenglai Yang, Xinyuan Gao, Shuai Li, Kun Yang, Jiangtao Hu, Hao Chen
Summary: A knowledge-guided framework using extreme gradient boosting machine (XGBoost) and interpretable tabular learning architecture (TabNet) was developed to model the carbon dioxide-oil minimum miscible pressure (MMP) in enhanced oil recovery projects. By integrating domain knowledge, the proposed models ensure predictions consistent with the domain knowledge. The experimental results demonstrate that KXGB is the most recommended solution for modeling MMP, while KTabNet has great potential.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Civil
Ying-Jie Zhu, Yan Bai, He Zhao
Summary: This paper proposes improved-GEP-based models for predicting the distortion control indices of curved composite girder bridges. The key parameters in the distortion equation are derived, and a parametric analysis is conducted. An improved GEP algorithm is proposed to establish the formulas for calculating the distortion control indices. Compared to traditional GEP, the proposed algorithm enhances the mining ability of the constants and coefficients and improves the global search ability. The proposed models agree with the finite element analysis results and distortion theory.
Article
Engineering, Chemical
Qian Sun, Aabiskar Bhusal, Na Zhang, Kapil Adhikari
Summary: In this study, a new method was proposed to estimate the MMP of shale oil/CO2 systems using huff-n-puff molecular dynamics simulations. The obtained results were in good agreement with experimental data. The oil recovery increased with the rise of reservoir temperature and slit height, but the MMP inside the nanopore was lower than the bulk counterpart due to confinement effect. CO2 huff-n-puff has the benefits of oil recovery and carbon sequestration.
CHEMICAL ENGINEERING SCIENCE
(2023)
Article
Energy & Fuels
Ming Li, Vincent W. S. Lim, Saif ZS. Al Ghafri, Nicholas Ling, Abdulrauf R. Adebayo, Eric F. May, Michael L. Johns
Summary: This study evaluates the application of nuclear magnetic resonance (NMR) techniques for estimating minimum miscibility pressure (MMP) between CO2 and different oil types, showing that NMR self-diffusion measurements provide more consistent MMP estimates compared to 1D imaging and NMR relaxation measurements.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2022)
Review
Energy & Fuels
Narendra Kumar, Marcio Augusto Sampaio, Keka Ojha, Hussein Hoteit, Ajay Mandal
Summary: This review extensively discusses the various technical aspects of enhancing oil production through the application of miscible CO2, identifying significant research gaps. It covers multiple aspects from theoretical analysis to laboratory experiments and field applications, providing valuable information for a better understanding of this topic.
Article
Engineering, Chemical
Alireza Rostami, Milad Arabloo, Shaghayegh Esmaeilzadeh, Amir H. Mohammadi
ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING
(2018)
Article
Energy & Fuels
Hamidreza Saghafi, Milad Arabloo
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2018)
Article
Energy & Fuels
Alireza Rostami, Amin Shokrollahi, Mohammad Hossein Ghazanfari
OIL & GAS SCIENCE AND TECHNOLOGY-REVUE D IFP ENERGIES NOUVELLES
(2018)
Article
Green & Sustainable Science & Technology
Alireza Rostami, Amin Shokrollahi, Zohre Esmaeili-Jaghdan, Mohammad Hossein Ghazanfari
ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY
(2019)
Article
Energy & Fuels
Hamid Reza Saghafi, Alireza Rostami, Milad Arabloo
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2019)
Article
Physics, Multidisciplinary
Amir Tabzar, Hossein Ziaee, Milad Arabloo, Mohammad Hossein Ghazanfari
EUROPEAN PHYSICAL JOURNAL PLUS
(2020)
Article
Engineering, Chemical
Farhad Gharagheizi, David S. Sholl
Summary: This paper systematically evaluates the accuracy of the ideal adsorbed solution theory (IAST) for gas adsorption using a large collection of binary experimental data, which will be valuable for future efforts to test or develop mixing theories that improve upon FAST. This analysis includes data from 63 gas mixtures of 37 different molecular species and 174 different adsorbents, making it the most systematic evaluation to date of the accuracy of IAST for gas adsorption.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Construction & Building Technology
Xiaofei Zhao, Minhaz Ur Rahman, Tharanga Dissanayaka, Farhad Gharagheizi, Carla Lacerda, Sanjaya Senadheera, Ronald C. Hedden, Gordon F. Christopher
Summary: The study investigates the effect of adding PP/PE copolymer modified asphalt binder on the ability to resist rutting in high temperatures. Results show that the PP/PE copolymer can significantly increase the rutting factor of asphalt binder within a specific temperature range, effectively reducing the risk of pavement rutting.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2021)
Article
Nanoscience & Nanotechnology
Farhad Gharagheizi, Zhenzi Yu, David S. Shoff
Summary: A collection of over 20,000 experimentally derived crystal structures for metal-organic frameworks (MOFs) without two- or three-dimensional covalently bonded networks has been developed. These structures are obtained from materials available at the Cambridge Crystallographic Data Centre. More than 12,000 of these structures have been verified to be solvent-free and in exact agreement with the stoichiometry of the synthesized materials. The study also reveals that there are more than 2,000 1D MOFs with a zero band gap, and that adsorbate-induced deformation plays a significant role in determining adsorption isotherms in these materials.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Chemistry, Physical
Afshin Tatar, Zohre Esmaeili-Jaghdan, Amin Shokrollahi, Abbas Zeinijahromi
Summary: This study used machine learning techniques to predict hydrogen solubility in hydrocarbons, finding that the GB model in ensemble methods has the highest accuracy. The results of the study contribute to a better understanding of hydrogen solubility in hydrocarbons.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Chemistry, Physical
Jifeng Sun, Farhad Gharagheizi, Hanjun Fang, Peter I. Ravikovitch, David S. Sholl
Summary: This study combines structure screening and high-throughput DFT calculations to investigate the adsorption of O2 and N2 in materials, identifying multiple materials that selectively bind O2 over N2 and suggesting design rules for tuning the O2 and N2 affinities in these materials.
JOURNAL OF PHYSICAL CHEMISTRY C
(2022)
Article
Energy & Fuels
Reza Behvandi, Afshin Tatar, Amin Shokrollahi, Abbas Zeinijahromi
Summary: The Group Method of Data Handling (GMDH) approach is used to predict hydrate formation temperature (T) in natural gas binary mixtures. A comprehensive database containing 728 data samples is compiled from 46 published experimental works. Different sets of input variables were assessed to find the best combination, and seven models were developed. The developed models performed better than existing correlations, with the model based on input Set #7 being the most accurate.
GEOENERGY SCIENCE AND ENGINEERING
(2023)
Article
Energy & Fuels
Mahsheed Rayhani, Afshin Tatar, Amin Shokrollahi, Abbas Zeinijahromi
Summary: By using machine learning algorithms, this study identified the most influential parameters on Minimum Miscibility Pressure (MMP) and developed reliable predictive models. The results can be used in industrial processes involving gas injection into hydrocarbon reservoirs to select the most relevant features for experimental and field trials design.
GEOENERGY SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Zohre Esmaeili-Jaghdan, Afshin Tatar, Amin Shokrollahi, Jan Bon, Abbas Zeinijahromi
Summary: In gas condensate reservoir research, accurate prediction of the dew point pressure (PDew) is crucial for gas and liquid assessment, reservoir characterisation, facility design, and simulation. Traditional methods are time-consuming and resource-intensive, while machine learning methods provide a reliable tool for PDew prediction. This study investigates the application of different decision tree-based methods for PDew prediction, and the results show that the novel Extremely Randomised Tree (ET) model outperforms existing models and equation of states (EoSs).
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Energy & Fuels
Alireza Rostami, Amin Shokrollahi, Khalil Shahbazi, Mohammad Hossein Ghazanfari
OIL & GAS SCIENCE AND TECHNOLOGY-REVUE D IFP ENERGIES NOUVELLES
(2019)
Article
Energy & Fuels
Yingna Du, Chen Huang, Wei Jiang, Qiangwei Yan, Yongfei Li, Gang Chen
Summary: In this study, anionic surfactants modified hydrotalcite was used as a flow improver for crude oil under low-temperature conditions. The modified hydrotalcite showed a significant viscosity reduction effect on crude oil. The mechanism of the modified hydrotalcite on viscosity and pour point of crude oil was explored through characterization and analysis of the modified hydrotalcite and oil samples.
Article
Energy & Fuels
Mohammad Saeid Rostami, Mohammad Mehdi Khodaei
Summary: In this study, a hybrid structure, MIL-53(Al)@MWCNT, was synthesized by combining MIL-53(Al) particles and -COOH functionalized multi-walled carbon nanotube (MWCNT). The hybrid structure was then embedded in a polyethersulfone (PES) polymer matrix to prepare a mixed matrix membrane (MMM) for CO2/CH4 and CO2/N2 separation. The addition of MWCNTs prevented MIL-53(Al) aggregation, improved membrane mechanical properties, and enhanced gas separation efficiency.
Article
Energy & Fuels
Yunlong Li, Desheng Huang, Xiaomeng Dong, Daoyong Yang
Summary: This study develops theoretical and experimental techniques to determine the phase behavior and physical properties of DME/flue gas/water/heavy oil systems. Eight constant composition expansion (CCE) tests are conducted to obtain new experimental data. A thermodynamic model is used to accurately predict saturation pressure and swelling factors, as well as the phase boundaries of N2/heavy oil systems and DME/CO2/heavy oil systems, with high accuracy.
Article
Energy & Fuels
Morteza Afkhamipour, Ebad Seifi, Arash Esmaeili, Mohammad Shamsi, Tohid N. Borhani
Summary: Non-conventional amines are being researched worldwide to overcome the limitations of traditional amines like MEA and MDEA. Adequate process and thermodynamic models are crucial for understanding the applicability and performance of these amines in CO2 absorption, but studies on process modeling for these amines are limited. This study used rate-based modeling and Deshmukh-Mather method to model CO2 absorption by DETA solution in a packed column, validated the model with experimental data, and conducted a sensitivity analysis of mass transfer correlations. The study also compared the CO2 absorption efficiency of DETA solution with an ionic solvent [bmim]-[PF6] and highlighted the importance of finding optimum operational parameters for maximum absorption efficiency.
Article
Energy & Fuels
Arastoo Abdi, Mohamad Awarke, M. Reza Malayeri, Masoud Riazi
Summary: The utilization of smart water in EOR operations has gained attention, but more research is needed to understand the complex mechanisms involved. This study investigated the interfacial tension between smart water and crude oil, considering factors such as salt, pH, asphaltene type, and aged smart water. The results revealed that the hydration of ions in smart water plays a key role in its efficacy, with acidic and basic asphaltene acting as intrinsic surfactants. The pH also influenced the interfacial tension, and the aged smart water's interaction with crude oil depended on asphaltene type, salt, and salinity.
Article
Energy & Fuels
Dongao Zhu, Kun Zhu, Lixian Xu, Haiyan Huang, Jing He, Wenshuai Zhu, Huaming Li, Wei Jiang
Summary: In this study, cobalt-based metal-organic frameworks (Co-based MOFs) were used as supports and co-catalysts to confine the NHPI catalyst, solving the leaching issue. The NHPI@Co-MOF with carboxyl groups exhibited stronger acidity and facilitated the generation of active oxygen radicals O2•, resulting in enhanced catalytic activity. This research provides valuable insights into the selection of suitable organic linkers and broadens the research horizon of MOF hybrids in efficient oxidative desulfurization (ODS) applications.
Article
Energy & Fuels
Edwin G. Hoyos, Gloria Amo-Duodu, U. Gulsum Kiral, Laura Vargas-Estrada, Raquel Lebrero, Rail Munoz
Summary: This study investigated the impact of carbon-coated zero-valent nanoparticle concentration on photosynthetic biogas upgrading. The addition of nanoparticles significantly increased microalgae productivity and enhanced nitrogen and phosphorus assimilation. The presence of nanoparticles also improved the quality of biomethane produced.
Article
Energy & Fuels
Yao Xiao, Asma Leghari, Linfeng Liu, Fangchao Yu, Ming Gao, Lu Ding, Yu Yang, Xueli Chen, Xiaoyu Yan, Fuchen Wang
Summary: Iron is added as a flocculant in wastewater treatment and the hydrothermal carbonization (HTC) of sludge produces wastewater containing Fe. This study investigates the effect of aqueous phase (AP) recycling on hydrochar properties, iron evolution and environmental assessment during HTC of sludge. The results show that AP recycling process improves the dewatering performance of hydrochar and facilitates the recovery of Fe from the liquid phase.
Article
Energy & Fuels
He Liang, Tao Wang, Zhenmin Luo, Jianliang Yu, Weizhai Yi, Fangming Cheng, Jingyu Zhao, Xingqing Yan, Jun Deng, Jihao Shi
Summary: This study investigated the influence of inhibitors (carbon dioxide, nitrogen, and heptafluoropropane) on the lower flammability limit of hydrogen and determined the critical inhibitory concentration needed for complete suppression. The impact of inhibitors on explosive characteristics was evaluated, and the inhibitory mechanism was analyzed with chemical kinetics. The results showed that with the increase of inhibitor quantity, the lower flammability limit of hydrogen also increased. The research findings can contribute to the safe utilization of hydrogen energy.
Article
Energy & Fuels
Zonghui Liu, Zhongze Zhang, Yali Zhou, Ziling Wang, Mingyang Du, Zhe Wen, Bing Yan, Qingxiang Ma, Na Liu, Bing Xue
Summary: In this study, high-performance solid catalysts based on phosphotungstic acid (HPW) supported on Zr-SBA-15 were synthesized and evaluated for the one-pot conversion of furfural (FUR) to γ-valerolactone (GVL). The catalysts were characterized using various techniques, and the ratio of HPW and Zr was found to significantly affect the selectivity of GVL. The HPW/Zr-SBA-15 (2-4-15) catalyst exhibited the highest GVL yield (83%) under optimized reaction conditions, and it was determined that a balance between Bronsted acid sites (BAS) and Lewis acid sites (LAS) was crucial for achieving higher catalytic performance. The reaction parameters and catalyst stability were also investigated.
Article
Energy & Fuels
Michael Stoehr, Stephan Ruoff, Bastian Rauch, Wolfgang Meier, Patrick Le Clercq
Summary: As part of the global energy transition, an experimental study was conducted to understand the effects of different fuel properties on droplet vaporization for various conventional and alternative fuels. The study utilized a flow channel to measure the evolution of droplet diameters over time and distance. The results revealed the temperature-dependent effects of physical properties, such as boiling point, liquid density, and enthalpy of vaporization, and showed the complex interactions of preferential vaporization and temperature-dependent influences of physical properties for multi-component fuels.
Article
Energy & Fuels
Yuan Zhuang, Ruikang Wu, Xinyan Wang, Rui Zhai, Changyong Gao
Summary: Through experimental validation and optimization of the chemical kinetic model, it was found that methanol can accelerate the oxidation reaction of ammonia, and methanol can be rapidly oxidized at high concentration. HO2 was found to generate a significant amount of OH radicals, facilitating the oxidation of methanol and ammonia. Rating: 7.5/10.
Article
Energy & Fuels
Radwan M. EL-Zohairy, Ahmed S. Attia, A. S. Huzayyin, Ahmed I. EL-Seesy
Summary: This paper presents a lab-scale experimental study on the impact of diethyl ether (DEE) as an additive to waste cooking oil biodiesel with Jet A-1 on combustion and emission features of a swirl-stabilized premixed flame. The addition of DEE to biodiesel significantly affects the flame temperature distribution and emissions. The W20D20 blend of DEE, biodiesel, and Jet A-1 shows similar flame temperature distribution to Jet A-1 and significantly reduces UHC, CO, and NOx emissions compared to Jet A-1.
Article
Energy & Fuels
Jiang Bian, Ziyuan Zhao, Yang Liu, Ran Cheng, Xuerui Zang, Xuewen Cao
Summary: This study presents a novel method for ammonia separation using supersonic flow and develops a mathematical model to investigate the condensation phenomenon. The results demonstrate that the L-P nucleation model accurately characterizes the nucleation process of ammonia at low temperatures. Numerical simulations also show that increasing pressure and concentration can enhance ammonia condensation efficiency.
Article
Energy & Fuels
Shiyuan Pan, Xiaodan Shi, Beibei Dong, Jan Skvaril, Haoran Zhang, Yongtu Liang, Hailong Li
Summary: Integrating CO2 capture with biomass-fired combined heat and power (bio-CHP) plants is a promising method for achieving negative emissions. This study develops a reliable data-driven model based on the Transformer architecture to predict the flowrate and CO2 concentration of flue gas in real time. The model validation shows high prediction accuracy, and the potential impact of meteorological parameters on model accuracy is assessed. The results demonstrate that the Transformer model outperforms other models and using near-infrared spectral data as input features improves the prediction accuracy.