G. Ignatenko, V. Turkin, O. Sviderskaya, V. Belyaev, S. Zubko
{"title":"REDUCING CARBON DIOXIDE EMISSIONS FROM MARINE DIESEL ENGINES BY OPTIMIZING FUEL SUPPLY AND COMBUSTION","authors":"G. Ignatenko, V. Turkin, O. Sviderskaya, V. Belyaev, S. Zubko","doi":"10.34046/aumsuomt105/27","DOIUrl":null,"url":null,"abstract":"The simulation of the working processes of the MAN D&T MC series marine diesel engine was carried out in \norder to reduce carbon dioxide emissions with exhaust gases. The purpose of the simulation was to find design \nand operational solutions that affect CO2 emissions. When performing a computational study, a mathematical \nmodel of a combined internal combustion engine implemented in the DIESEL-RK computer program was used. The studied variables are the compression ratio, the advance angle and the duration of fuel injection, the values \nof which can be set without making significant changes to the engine design. Mathematical models are obtained \nin the form of regression equations that describe the effect of the studied fuel supply parameters (compression \nratio, fuel injection advance angle and fuel injection duration) on the target functions - specific carbon dioxide \nemission and effective power of the 6S60MC diesel engine. To determine the coefficients of the regression \nequation, planning of a complete factorial experiment of the second order is implemented. In order to find the \nminimum value of carbon dioxide emissions using the generalized reduced gradient method, the problem of \nchoosing the optimal values of the compression ratio, fuel injection duration and fuel injection advance angle \nfor a given effective power of a 6S60MC marine diesel engine is solved. It is shown that, for example, with an \nengine power of 10,000 kW, the reduction in carbon dioxide emissions by optimizing the specified fuel supply \nparameters will be 7.37%","PeriodicalId":19521,"journal":{"name":"Operation of Maritime Transport","volume":"80 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operation of Maritime Transport","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34046/aumsuomt105/27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The simulation of the working processes of the MAN D&T MC series marine diesel engine was carried out in
order to reduce carbon dioxide emissions with exhaust gases. The purpose of the simulation was to find design
and operational solutions that affect CO2 emissions. When performing a computational study, a mathematical
model of a combined internal combustion engine implemented in the DIESEL-RK computer program was used. The studied variables are the compression ratio, the advance angle and the duration of fuel injection, the values
of which can be set without making significant changes to the engine design. Mathematical models are obtained
in the form of regression equations that describe the effect of the studied fuel supply parameters (compression
ratio, fuel injection advance angle and fuel injection duration) on the target functions - specific carbon dioxide
emission and effective power of the 6S60MC diesel engine. To determine the coefficients of the regression
equation, planning of a complete factorial experiment of the second order is implemented. In order to find the
minimum value of carbon dioxide emissions using the generalized reduced gradient method, the problem of
choosing the optimal values of the compression ratio, fuel injection duration and fuel injection advance angle
for a given effective power of a 6S60MC marine diesel engine is solved. It is shown that, for example, with an
engine power of 10,000 kW, the reduction in carbon dioxide emissions by optimizing the specified fuel supply
parameters will be 7.37%