scholarly journals Analysis of the Pre-Injection System of a Marine Diesel Engine Through Multiple-Criteria Decision-Making and Artificial Neural Networks

2021 ◽  
Vol 28 (4) ◽  
pp. 88-96
Author(s):  
C.G. Rodriguez ◽  
M.I. Lamas ◽  
J.D. Rodriguez ◽  
A. Abbas
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Injection System ◽  
Marine Diesel Engine ◽  
Oxides Of Nitrogen ◽  
Marine Engines ◽  
Marine Diesel ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Abstract The present work proposes several pre-injection patterns to reduce nitrogen oxides in the Wärtsilä 6L 46 marine engine. A numerical model was carried out to characterise the emissions and consumption of the engine. Several pre-injection quantities, durations, and starting instants were analysed. It was found that oxides of nitrogen can be noticeably reduced but at the expense of increasing consumption as well as other emissions such as carbon monoxide and hydrocarbons. According to this, a multiple-criteria decision-making (MCDM) model was established to select the most appropriate parameters. Besides, an artificial neural network (ANN) was developed to complement the results and analyse a huge quantity of alternatives. This hybrid MCDM-ANN methodology proposed in the present work constitutes a useful tool to design new marine engines.

scholarly journals Optimization of a Multiple Injection System in a Marine Diesel Engine through a Multiple-Criteria Decision-Making Approach

2020 ◽  
Vol 8 (11) ◽  
pp. 946 ◽  
Author(s):  
Maria Isabel Lamas ◽  
Laura Castro-Santos ◽  
Carlos G. Rodriguez
Keyword(s):  
Decision Making ◽  
Standard Deviation ◽  
Diesel Engine ◽  
Multiple Criteria Decision Making ◽  
Entropy Method ◽  
Multiple Criteria ◽  
Injection System ◽  
Marine Diesel Engine ◽  
Weighting Method ◽  
Marine Diesel

In this work, a numerical model was developed to analyze the performance and emissions of a marine diesel engine, the Wärtsilä 6L 46. This model was validated using experimental measurements and was employed to analyze several pre-injection parameters such as pre-injection rate, duration, and starting instant. The modification of these parameters may lead to opposite effects on consumption and/or emissions of nitrogen oxides (NOx), carbon monoxide (CO), and hydrocarbons (HC). According to this, the main goal of the present work is to employ a multiple-criteria decision-making (MCDM) approach to characterize the most appropriate injection pattern. Since determining the criteria weights significantly influences the overall result of a MCDM problem, a subjective weighting method was compared with four objective weighting methods: entropy, CRITIC (CRiteria Importance Through Intercriteria Correlation), variance, and standard deviation. The results showed the importance of subjectivism over objectivism in MCDM analyses. The CRITIC, variance, and standard deviation methods assigned more importance to NOx emissions and provided similar results. Nevertheless, the entropy method assigned more importance to consumption and provided a different injection pattern.

scholarly journals Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks

2021 ◽  
Vol 18 (23) ◽  
pp. 12823
Author(s):  
María Isabel Lamas Galdo ◽  
Javier Telmo Miranda ◽  
José Manuel Rebollido Lorenzo ◽  
Claudio Giovanni Caccia
Keyword(s):  
Decision Making ◽  
Internal Combustion Engines ◽  
Multiple Criteria Decision Making ◽  
Cooling Water ◽  
Multiple Criteria ◽  
Water Addition ◽  
Cooling Water Temperature ◽  
Marine Diesel ◽  
Artificial Neural ◽  
Gas Recirculation

The present work proposes several modifications to optimize both emissions and consumption in a commercial marine diesel engine. A numerical model was carried out to characterize the emissions and consumption of the engine under several performance parameters. Particularly, five internal modifications were analyzed: water addition; exhaust gas recirculation; and modification of the intake valve closing, overlap timing, and cooling water temperature. It was found that the result on the emissions and consumption presents conflicting criteria, and thus, a multiple-criteria decision-making model was carried out to characterize the most appropriate parameters. In order to analyze a high number of possibilities in a reasonable time, an artificial neural network was developed.

scholarly journals Selection of an Appropriate Pre-Injection Pattern in a Marine Diesel Engine Through a Multiple-Criteria Decision Making Approach

2020 ◽  
Vol 10 (7) ◽  
pp. 2482 ◽  
Author(s):  
María Isabel Lamas Galdo ◽  
Laura Castro-Santos ◽  
Carlos G. Rodríguez Vidal
Keyword(s):  
Decision Making ◽  
Diesel Engine ◽  
Multiple Criteria Decision Making ◽  
Injection Rate ◽  
Multiple Criteria ◽  
Injection Duration ◽  
Formal Tool ◽  
Marine Diesel ◽  
Selection Of ◽  
Injection Strategies

In the present work, a numerical model was developed to analyze a commercial diesel engine. The adequacy of this model was validated using experimental results. This model was employed to study several pre-injection strategies. Particularly, the pre-injection rate, duration and starting instant were analyzed in the ranges 5% to 25%, 1° to 5° and −22° to −18°, respectively. The effect on consumption and emissions of NOx, CO, and HC wereas evaluated. Since some of these configurations have opposite effects on consumption and/or emissions, it is necessary to develop a formal tool to characterize the most appropriate injection pattern. To this end, a multiple-criteria decision making approach was employed. It was found that the injection duration must remain as low as possible due to significant reductions in NOx. The most appropriate injection pattern resulted 1° pre-injection duration, 20% pre-injection rate, and −19° pre-injection starting instant. This configuration leads to increments of 6.7% in consumption, 3.47% in CO, and 3.83% in HC but reduces NOx by 34.67% in comparison with the case without pre-injection.

scholarly journals Green Supplier Selection Using Fuzzy Multiple-Criteria Decision-Making Methods and Artificial Neural Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-26
Author(s):  
Tina Gegovska ◽  
Rasit Koker ◽  
Tarik Cakar
Keyword(s):  
Neural Networks ◽  
Decision Making ◽  
Artificial Neural Networks ◽  
Supplier Selection ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Manufacturing Firm ◽  
Green Supplier Selection ◽  
Artificial Neural ◽  
Fuzzy Mcdm

In recent years, environmental awareness has increased considerably, and in order to decrease endangerments such as air and water pollution, and also global warming, green procurement should be employed. Therefore, in the assessment of suppliers, their environmental performance should be taken into consideration along with other criteria for supplier selection. Raising awareness of sustainability in production and conservation and protection of the environment is very important both for the whole environment and for the company itself by increasing its competitive advantage. And, one of the steps to achieve this is for the companies to try to select green suppliers. So, the purpose of this study is to raise awareness and tackle the need for green supplier selection and, using multiple-criteria decision-making models, to elaborate a case study regarding this. A survey was conducted in a manufacturing firm. The data were analysed, and fuzzy MCDM (multicriteria decision-making) methods and artificial neural networks were implemented. Fuzzy methods are the fuzzy analytic hierarchy process (fuzzy AHP), fuzzy TOPSIS, and fuzzy ELECTRE. ANN supports the result of fuzzy MCDM models from the profit side. ANN can make the best estimate of the current year based on historical data. Fuzzy MCDM methods will also find good solutions using the available data but will produce different solutions as there are different decision-making methods. It is aimed to produce a synergy from the solutions obtained here and to produce a better solution. Instead of a single method, it would be more accurate to produce a better solution than the solution provided by all of them. The dominant result has been obtained using the committee fuzzy MCDM and ANN to select the best green supplier.

Sign in / Sign up

Export Citation Format

Share Document