Exhaust emission characteristics of a diesel engine on gasoline fumigation: an experimental investigation and evaluation using the MCDM method

Hoseinpour, Marziyeh; Sadrnia, Hassan; Ghobadian, Barat; Tabasizadeh, Mohammad

doi:10.1007/s13762-018-1667-1

Cited by 6 publications

(2 citation statements)

References 37 publications

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“…Multiple criteria decision making (MCDM) is a methodology used to solve complex problems (Hoseinpour, Sadrnia, Ghobadian, & Tabasizadeh, 2019). Entropy and TOPSIS in MCDM have been widely applied to solve complex project selection and evaluation.…”

Section: Constructing the Decision-making Modelmentioning

confidence: 99%

Optimization Plan for Excess Warehouse Storage in E-Commerce–based Plant Shops: A Case Study for Chinese Plant Industrial

Lin¹,

Cho

et al. 2019

Journal of Business Economics and Management

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The rapid development of e-commerce in China has played a critical role in the development of the national economy and ongoing modernization. The plant industry is unique among industries that employ e-commerce sales models because its products exhibit special characteristics such as high death and damage rates. Therefore, its e-commerce and logistical requirements are stricter than in other industries and, as a result, excess warehouse storage can be extremely difficult for e-commerce-based plant shops to manage. Numerous studies have indicated the need to identify a product's most up-to-date market conditions, as well as the type, function, and size of warehouses. Therefore, based on a case study, this study proposes an optimization plan for solving excess warehouse storage in e-commerce-based plant shops. First, sales volume data of the case company, Enterprise A, were analyzed to predict future sales. Then, entropy and the technique for order preference by similarity to an ideal solution were used to construct the decision-making model. Finally, a cloud warehouse-based optimization plan was proposed to solve excess warehouse storage in e-commerce-based plant shops. This plan can serve as a reference for decision-makers or executives in e-commerce-based plant shops when handling excess warehouse storage.

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Section: Constructing the Decision-making Modelmentioning

confidence: 99%

Optimization Plan for Excess Warehouse Storage in E-Commerce–based Plant Shops: A Case Study for Chinese Plant Industrial

Lin¹,

Cho

et al. 2019

Journal of Business Economics and Management

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“…The multi-criteria decision-making method was used to evaluate diesel exhaust emission characteristics by Hoseinpour et al [9], while gasoline fumigation was added to reduce pollutant emissions under different operating conditions. A plant-specific multi-year and multi-parameter coal power stack emission model has been proposed by Walvekar and Gurjar [10] using the emission factorbased approach.…”

Section: Introductionmentioning

confidence: 99%

Response surface methodology-based model for prediction of NO and NO2 concentrations in nonthermal plasma-treated diesel exhaust

Allamsetty

Mohapatro

2019

SN Appl. Sci.

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Nonthermal plasma (NTP) technique for diesel exhaust emission control has been in the interest of the researchers from the last two decades, and it almost became a laboratory-proven technique for its efficiency over conventional techniques. A prior prediction of effectiveness of the process may lead to overcome the constraints in bringing this technique to real-time applications of diesel exhaust pollution control. In this present study, an attempt is made to find out the most dominating parameters and to predict the sum of NO and NO 2 concentrations in NTP-treated diesel exhaust with respect to variations in operating parameter values using response surface methodology (RSM). Experiments have been conducted following 3 N full factorial design and collected the data by varying voltage, flow rate, temperature, discharge gap and initial (NO + NO 2 ) concentrations. The regression coefficients of the RSM-based mathematical model have been obtained by training it using these experimental data. The root-mean-square error (RMSE) is 4.7 ppm during the training. When this model is tested for a data other than that given during training (test data), the RMSE is 5.6 ppm. Further, the results are also compared with the model derived using the only available method in the literature, i.e., dimensional analysis, and found to be performing better.

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Cu–ZSM5 zeolite as an environmental emission reducing catalyst for biodiesel

Elavarasan

Karthikeyan

2021

Int. J. Environ. Sci. Technol.

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Exhaust emission characteristics of a diesel engine on gasoline fumigation: an experimental investigation and evaluation using the MCDM method

Cited by 6 publications

References 37 publications

Optimization Plan for Excess Warehouse Storage in E-Commerce–based Plant Shops: A Case Study for Chinese Plant Industrial

Optimization Plan for Excess Warehouse Storage in E-Commerce–based Plant Shops: A Case Study for Chinese Plant Industrial

Response surface methodology-based model for prediction of NO and NO2 concentrations in nonthermal plasma-treated diesel exhaust

Cu–ZSM5 zeolite as an environmental emission reducing catalyst for biodiesel

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