Multi-objective optimization of micro co-generation spark-ignition engine fueled by biogas with various CH4 / CO2 content based on GA-ANN and decision-making approaches

Ghersi, Djamal Eddine; Loubar, Khaled; Amoura, Meriem; Tazerout, Mohand

doi:10.1016/j.jclepro.2021.129739

Cited by 16 publications

(3 citation statements)

References 38 publications

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“…It has been proven that TOPSIS has achieved satisfactory results in the studies. For detailed information, please refer to Ghersi et al. (2021) and Ribeiro et al.…”

Section: Model and Algorithmmentioning

confidence: 99%

Multi-objective optimization of tribological properties of camshaft bearing pairs using DNN coupled with NSGA-II algorithm and TOPSIS

Zhao,

Li,

Xie

et al. 2024

ILT

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Purpose This study aims to propose an optimization framework using deep neural networks (DNN) coupled with nondominated sorting genetic algorithm II and technique for order preference by similarity to an ideal solution method to improve the tribological properties of camshaft bearing pairs of internal combustion engine. Design/methodology/approach A lubrication model based on the theory of elastohydrodynamic lubrication and flexible multibody dynamics was developed for a V6 diesel engine. Setting DNN model as fitness function, the multi-objective optimization genetic algorithm and decision-making method were used to optimize the bearing pair structure with the goal of minimizing the total friction loss and the difference of the average values of minimum oil film thickness. Findings The results show that the lubrication state corresponding to the optimized bearing pair structure is elastohydrodynamic lubrication. Compared with the original structure, the optimized structure significantly reduces the total friction loss. Originality/value The optimized performance and corresponding structural parameters are obtained, and the optimization results were verified through multibody dynamics simulation. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0417/

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“…It has been proven that TOPSIS has achieved satisfactory results in the studies. For detailed information, please refer to Ghersi et al. (2021) and Ribeiro et al.…”

Section: Model and Algorithmmentioning

confidence: 99%

Multi-objective optimization of tribological properties of camshaft bearing pairs using DNN coupled with NSGA-II algorithm and TOPSIS

Zhao,

Li,

Xie

et al. 2024

ILT

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“…For instance, PSO is applied to perform validation calculations on optimization schemes [24], conduct the multi-objective optimization of equipment capacity and operation [25] and solve the extended travelling salesman problem [26]. GA is applied to assess system reliability [27], estimate energy plant size [28] and determine optimal operating parameters [29].…”

Section: Introductionmentioning

confidence: 99%

An Investment Decision-Making Approach for Power Grid Projects: A Multi-Objective Optimization Model

Gao

2022

Energies

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With the reform of the power system in China, investments in power grid projects across the whole power system are increasing. However, there are various objectives to achieve in the investment decision processes of power grid projects, so the rational investments of a grid project can be seen as a multi-objective optimization problem. Meanwhile, these issues have rarely been studied at home and abroad, and this paper will fill this gap. As a result, this study critically analyzed the application of a multi-objective optimization model to power grid investment. Firstly, the objective factors of grid investments were explored, which were quantified through quantitative methods. Secondly, based on the characteristics of power grid investment, a multi-objective optimization model was established, and the assumptions and constraints of the model were presented. Finally, NSGA-II was used for solving the multi-objective optimization model. The results show that: (1) Multi-objective optimization models are suitable for the study of and deriving solutions for power grid investment by establishing suitable objective functions, assumptions and constraints, (2) According to the conventional steps of NSGA-II, suitable steps can be established to search for an optimal solution to the objective set of a power grid investment and (3) Due to the different concerns of different project scenarios, Pareto frontier solutions can be selected as the practical references of power grid projects. Therefore, the solution set makes the implementation scheme more flexible.

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“…Mažėjant metano koncentracijai biodujose nuo 100 %(v) iki 55 %(v) ir esant mažai apkrovai (droselinė sklendė atidaryta 5,5 %) UPK reikia didinti nuo 25 ⁰AV iki 40 ⁰AV norint išlaikyti maksimalų variklio efektyvųjį naudingumo koeficientą. Didinant apkrovą ir droselinę sklendę praveriant iki 35 % metano koncentracija biodujose turi mažesnį poveikį variklio efektyviajam naudingumo koeficientui ir pastebimas mažesnis UPK reguliavimo poreikis kintant biodujų sudėčiai (Ghersi et al, 2021).…”

Section: Biodujų Sudėtis Ir Savybėsunclassified

Biodujomis veikiančio kibirkštinio uždegimo variklio ekologinių ir energinių rodiklių gerinimas

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Vadovas doc. dr. Saugirdas PUKALSKAS (Vilniaus Gedimino technikos universitetas, transporto inžinerija -T 003). Vilniaus Gedimino technikos universiteto Transporto inžinerijos mokslo krypties disertacijos gynimo taryba: Pirmininkas prof. dr. Gintautas BUREIKA (Vilniaus Gedimino technikos universitetas, transporto inžinerija -T 003). Nariai: prof. dr. Stasys SLAVINSKAS (Vytauto Didžiojo universitetas, transporto inžinerija -T 003), dr. Nerijus STRIŪGAS (Lietuvos energetikos institutas, energetika ir termoinžinerija -T 006), prof. habil. dr. Stanislaw SZWAJA (Čenstakavos technologijos universitetas, Lenkija, energetika ir termoinžinerija -T 006), doc. dr. Gediminas VAIČIŪNAS (Vilniaus Gedimino technikos universitetas, transporto inžinerija -T 003). Disertacija bus ginama viešame Transporto inžinerijos mokslo krypties disertacijos gynimo tarybos posėdyje 2022 m. rugpjūčio 31 d. 10 val. Vilniaus Gedimino technikos universiteto senato posėdžių salėje.

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Multi-objective optimization of micro co-generation spark-ignition engine fueled by biogas with various CH4 / CO2 content based on GA-ANN and decision-making approaches

Cited by 16 publications

References 38 publications

Multi-objective optimization of tribological properties of camshaft bearing pairs using DNN coupled with NSGA-II algorithm and TOPSIS

Multi-objective optimization of tribological properties of camshaft bearing pairs using DNN coupled with NSGA-II algorithm and TOPSIS

An Investment Decision-Making Approach for Power Grid Projects: A Multi-Objective Optimization Model

Biodujomis veikiančio kibirkštinio uždegimo variklio ekologinių ir energinių rodiklių gerinimas

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