Multi-input multi-output machine learning predictive model for engine performance and stability, emissions, combustion and ignition characteristics of diesel-biodiesel-gasoline blends

Article Thermodynamics

Integration of artificial neural network, multi-objective genetic algorithm and phenomenological combustion modelling for effective operation of biodiesel blends in an automotive engine

Sundararajan Rajkumar et al.

Summary: In this study, researchers combined artificial neural networks and genetic algorithms to develop a method for predicting engine parameters, successfully determining the optimal biodiesel blend ratio, with good prediction performance.

ENERGY (2022)

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Article Green & Sustainable Science & Technology

Experimental investigation on combustion and (regulated and unregulated) emissions performance of a common-rail diesel engine using partially hydrogenated biodiesel-ethanol-diesel ternary blend

Lei Zuo et al.

Summary: This study aimed to establish a partial hydrogenated biodiesel-ethanol-diesel ternary blend and investigate its combustion performance and emissions. The results revealed that the ternary blend exhibited different properties compared to the binary blend in certain aspects.

RENEWABLE ENERGY (2022)

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Article Engineering, Multidisciplinary

Review of artificial neural networks for gasoline, diesel and homogeneous charge compression ignition engine

Ibham Veza et al.

Alexandria Engineering Journal (2022)

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Article Thermodynamics

Artificial neural networks modeling of combustion parameters for a diesel engine fueled with biodiesel fuel

Ozer Can et al.

Summary: In this study, various artificial neural networks were utilized to predict the combustion characteristics of a diesel engine. The results showed that all the proposed neural networks had high accuracy in predicting the parameters, and the MLP architecture with the LM algorithm achieved the best results.

ENERGY (2022)

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Article Energy & Fuels

Rigorous modeling of frictional pressure loss in inclined annuli using artificial intelligence methods

Amin Bemani et al.

Summary: This study proposes three machine learning-based algorithms for calculating frictional pressure loss in gas-driven drilling fluids with cuttings in inclined wells. The models show excellent performance in predicting frictional pressure loss for inclined wells.

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2022)

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Article Green & Sustainable Science & Technology

How environmental regulations affect the development of green finance: Recent evidence from polluting firms in China

Yong Xu et al.

Summary: This study focuses on Chinese A-share polluting companies and finds that environmental regulations have a positive impact on the development of green finance, particularly through short-term or long-term external financing. However, the effect of environmental regulations varies across different regions and types of companies, and green finance is also influenced by greenwashing.

RENEWABLE ENERGY (2022)

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Article Thermodynamics

Grasshopper optimization algorithm for diesel engine fuelled with ethanol-biodiesel-diesel blends

Ibham Veza et al.

Summary: The recently invented grasshopper optimization algorithm (GOA) was used to optimize the performance and emissions of a diesel engine running on a ternary fuel blend. Regression modeling was used to calculate the mathematical equations between the factors (ethanol ratio, biodiesel ratio, engine load) and the responses (BSFC, BTE, HC, CO2, NOx, CO). The results showed that the grasshopper optimization algorithm successfully maximized BTE and minimized the other responses, indicating its potential for improving engine performance and emissions.

CASE STUDIES IN THERMAL ENGINEERING (2022)

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Article Engineering, Environmental

Effect of waste cooking oil biodiesel blending with gasoline and kerosene on diesel engine performance, emissions and combustion characteristics

M. S. Gad et al.

Summary: Blending waste cooking oil biodiesel with gasoline or kerosene can enhance diesel engine performance parameters, improve combustion characteristics, and reduce emissions.

PROCESS SAFETY AND ENVIRONMENTAL PROTECTION (2021)

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Article Biotechnology & Applied Microbiology

Evaluation of engine performance and emission of African pear seed oil (APO) biodiesel and its prediction via multi-input-multi-output artificial neural network (ANN) and sensitivity analysis

Callistus Nonso Ude et al.

Summary: The evaluation of engine performance and emission of biodiesel produced from African pear seed oil and its prediction using MIMO artificial neural network were studied. The results showed that blending APO methyl ester with petro-diesel improved engine efficiency and emissions. The MIMO model demonstrated better performance in predicting engine performance compared to the MISO model.

BIOFUELS BIOPRODUCTS & BIOREFINING-BIOFPR (2021)

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Article Energy & Fuels

Experimental and computational analysis of combustion characteristics of a diesel engine fueled with diesel-tomato seed oil biodiesel blends

Rahim Karami et al.

Summary: This study conducted combustion analysis experiments on a four-cylinder diesel engine fueled by tomato seed oil biodiesel blends, with results indicating that B10 is the optimal mixture for reducing greenhouse gas emissions while maintaining engine performance. Both an artificial neural network model and AVL simulation yielded results that agree satisfactorily with experimental values.

FUEL (2021)

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Article Engineering, Multidisciplinary

Prediction of pressure in different two-phase flow conditions: Machine learning applications

Ehsan Khamehchi et al.

Summary: Accurate prediction of pressure is crucial in the petroleum industry for various applications, and machine learning approaches such as Gradient tree boosting and Extreme Learning Machine have been shown to have excellent performance in oil field calculations. Well-head pressure is identified as the most effective parameter in determining bottom-hole pressure.

MEASUREMENT (2021)

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Article Thermodynamics

On-the-fly artificial neural network for chemical kinetics in direct numerical simulations of premixed combustion

Cheng Chi et al.

Summary: The developed on-the-fly artificial neural network framework efficiently handles chemical reaction terms in premixed and igniting flames, accurately predicts flame characteristics, and significantly reduces computational times compared to traditional methods. This approach reduces computational times by almost 5 times and maintains errors below 1% compared to standard methods.

COMBUSTION AND FLAME (2021)

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Review Thermodynamics

Machine learning technology in biodiesel research: A review

Mortaza Aghbashlo et al.

Summary: Biodiesel research utilizes machine learning techniques, such as artificial neural networks, to address complex production and control challenges. ML technology is applied in modeling transesterification processes, physico-chemical characteristics, and internal combustion engine studies. Future research may focus on real-time monitoring and control of biodiesel systems to enhance production efficiency and environmental sustainability.

PROGRESS IN ENERGY AND COMBUSTION SCIENCE (2021)

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Article Engineering, Chemical

A comprehensive insight into the application of machine learning approaches in predicting the separation efficiency of hydrocyclones

Mohammad Zandieh et al.

Summary: This study investigates the separation efficiency of hydrocyclones using machine learning approaches and optimization methods, aiming to enhance prediction accuracy. The results confirm the feasibility and accuracy of the research, with in-depth analyses on the effectiveness of the algorithms.

DESALINATION AND WATER TREATMENT (2021)

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Article Engineering, Multidisciplinary

An experimental based artificial neural network modeling in prediction of optimum combustion, performance, and emission from diesel engine operated with three biodiesels

Aditya Kolakoti

Summary: This study aimed to improve diesel engine performance and regulate harmful emissions by examining palm oil biodiesel, waste cooking biodiesel, and animal fat biodiesel. Results showed that biodiesels had better fuel properties compared to diesel, but with increased fuel consumption and NOx emissions. Waste cooking biodiesel was selected as the best choice based on ANN modeling predictions.

WORLD JOURNAL OF ENGINEERING (2021)

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Article Computer Science, Artificial Intelligence

Investigating the impact of data normalization on classification performance

Dalwinder Singh et al.

APPLIED SOFT COMPUTING (2020)

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Article Green & Sustainable Science & Technology

Enhanced leader adaptive velocity particle swarm optimisation based global maximum power point tracking technique for a PV string under partially shaded conditions

Dileep Krishna Mathi et al.

IET RENEWABLE POWER GENERATION (2020)

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Article Green & Sustainable Science & Technology

Artificial neural network modeling of performance, emission, and vibration of a CI engine using alumina nano-catalyst added to diesel-biodiesel blends

Seyyed Hassan Hosseini et al.

RENEWABLE ENERGY (2020)

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Article Green & Sustainable Science & Technology

Influence of alternative fuels on combustion and characteristics of particulate matter morphology in a compression ignition diesel engine

Mohammed A. Fayad et al.

RENEWABLE ENERGY (2020)

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Review Chemistry, Applied

Review on dynamic process modeling of gasification based biorefineries and bio-based heat & power plants

Konstantinos Atsonios et al.

FUEL PROCESSING TECHNOLOGY (2020)

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Article Green & Sustainable Science & Technology

Modeling of cetane number of biodiesel from fatty acid methyl ester (FAME) information using GA-, PSO-, and HGAPSO- LSSVM models

Amin Bemani et al.

RENEWABLE ENERGY (2020)

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Article Thermodynamics

A hybrid ANN-Fuzzy approach for optimization of engine operating parameters of a CI engine fueled with diesel-palm biodiesel-ethanol blend

Suman Dey et al.

ENERGY (2020)

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Article Chemistry, Applied

Using ethanol for continuous biodiesel production with trace catalyst and CO2 co-solvent

Aso A. Hassan et al.

FUEL PROCESSING TECHNOLOGY (2020)

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Article Thermodynamics

Enhancement the combustion aspects of a CI engine working with Jatropha biodiesel/decanol/propanol ternary combinations

Ahmed EL-Seesy et al.

ENERGY CONVERSION AND MANAGEMENT (2020)

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Article Energy & Fuels

ANN modeling for justification of thermodynamic analysis of experimental applications on combustion parameters of a diesel engine using diesel and safflower biodiesel fuels

Bahattin Iscan

FUEL (2020)

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Article Thermodynamics

Multi-input multi-output (MIMO) ANN and Nelder-Mead's simplex based modeling of engine performance and combustion emission characteristics of biodiesel-diesel blend in CI diesel engine

Chizoo Esonye et al.

APPLIED THERMAL ENGINEERING (2019)

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Article Energy & Fuels

An insight into the estimation of fatty acid methyl ester based biodiesel properties using a LSSVM model

Razieh Razavi et al.

FUEL (2019)

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Article Thermodynamics

An investigation on gasoline compression ignition (GCI) combustion in a heavy-duty diesel engine using gasoline/hydrogenated catalytic biodiesel blends

Yanzhi Zhang et al.

APPLIED THERMAL ENGINEERING (2019)

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Review Green & Sustainable Science & Technology

A review of greenhouse gas emission profiles, dynamics, and climate change mitigation efforts across the key climate change players

Xiaosong Zheng et al.

JOURNAL OF CLEANER PRODUCTION (2019)

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Review Energy & Fuels

A review of global current scenario of biodiesel adoption and combustion in vehicular diesel engines

Oyetola Ogunkunle et al.

ENERGY REPORTS (2019)

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Article Multidisciplinary Sciences

Performance comparison of neural network training algorithms in the modeling properties of steel fiber reinforced concrete

T. F. Awolusi et al.

HELIYON (2019)

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Article Thermodynamics

Prediction of exhaust emission in transient conditions of a diesel engine fueled with animal fat using Artificial Neural Network and Symbolic Regression

Aida Dominguez-Saez et al.

ENERGY (2018)

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Review Green & Sustainable Science & Technology

A review on the application of response surface method and artificial neural network in engine performance and exhaust emissions characteristics in alternative fuel

I. M. Yusri et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2018)

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Article Green & Sustainable Science & Technology

Effect of ternary blends of bio-ethanol, diesel and castor oil on performance, emission and combustion in a CI engine

T. Prakash et al.

RENEWABLE ENERGY (2018)

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Article Chemistry, Multidisciplinary

Prediction of solubility of N-alkanes in supercritical CO2 using RBF-ANN and MLP-ANN

Mahdi Abdi-Khanghah et al.

JOURNAL OF CO2 UTILIZATION (2018)

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Article Thermodynamics

Energy and exergy analyses of a diesel engine fueled with diesel, biodiesel-diesel blend and gasoline fumigation

Marziyeh Hoseinpour et al.

ENERGY (2017)

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Article Engineering, Mechanical

Sensitivity analysis of the factors affecting the discharge capacity of side weirs in trapezoidal channels using extreme learning machines

Hamed Azimi et al.

FLOW MEASUREMENT AND INSTRUMENTATION (2017)

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Review Green & Sustainable Science & Technology

Effect of different technologies on combustion and emissions of the diesel engine fueled with biodiesel: A review

Jiaqiang E et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2017)

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Article Energy & Fuels

Optimisation of operating parameters of DI-CI engine fueled with second generation Bio-fuel and development of ANN based prediction model

S. V. Channapattana et al.

APPLIED ENERGY (2017)

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Multi-input multi-output machine learning predictive model for engine performance and stability, emissions, combustion and ignition characteristics of diesel-biodiesel-gasoline blends

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