Modeling and Multi-Objective Optimization of NOx Conversion Efficiency and NH3 Slip for a Diesel Engine

Liu, Bo; Yan, Fuwu; Hu, Jie; Turkson, Richard Fiifi; Lin, Feng

doi:10.3390/su8050478

Cited by 22 publications

(9 citation statements)

References 34 publications

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“…Data driven prognostics are based on machine learning algorithms applied to degradation data collected, without making any assumption about the physics of failure or the damage accumulation model. Several machine learning techniques have been successfully applied for RUL estimation in the automotive industry, including Principle Components Analysis (Liu et al, 2016), Extreme Learning Machine, Support Vector Machines and Artificial Neural Networks (Fink et al, 2015), k-NN classifier and Bayesian filter (Mossalam et al, 2016), and random forest (Prytz et al, 2015). See Lee et al (2014) for a wider review of examples of data driven methods for RUL prediction.…”

Section: Figure 3 Prognostics Based On Rulmentioning

confidence: 99%

Automotive IVHM: Towards Intelligent Personalised Systems Healthcare

Campean

Neagu

Doikin

et al. 2019

Proc. Int. Conf. Eng. Des.

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Underpinned by a contemporary view of automotive systems as cyber-physical systems, characterised by progressively open architectures increasingly defined by their interaction with the users and the smart environment, this paper provides a critical and up-to-date review of automotive Integrated Vehicle Health Management (IVHM) systems. The paper discusses the challenges with prognostics and intelligent health management of automotive systems, and proposes a high-level framework, referred to as the Automotive Healthcare Analytic Factory, to systematically collect and process heterogeneous data from across the product lifecycle, towards actionable insight for personalised healthcare of systems.

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Section: Figure 3 Prognostics Based On Rulmentioning

confidence: 99%

Automotive IVHM: Towards Intelligent Personalised Systems Healthcare

Campean

Neagu

Doikin

et al. 2019

Proc. Int. Conf. Eng. Des.

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“…In sewage sludge incineration facilities, selective non-catalytic reduction (SNCR) is utilized to reduce the emission of nitrogen oxides (NOx). In the case of SNCR, NOx can be reduced, but if excessively operated, NH 3 will be generated and discharged into the atmosphere [ 5 , 6 , 7 , 8 ]. NH 3 is one of the secondary products of ultrafine particles and is considered to be an odorous air pollutant [ 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Estimating the Characteristics and Emission Factor of Ammonia from Sewage Sludge Incinerator

Kang

Roh

2021

IJERPH

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In the case of sewage sludge, as direct landfilling was recently prohibited, it is treated through incineration. Among the air pollutants discharged through the incineration of sewage sludge, NOx and SOx are considered secondary substances of PM2.5 and are being managed accordingly. However, NH3, another of the secondary substances of PM2.5, is not well managed, and the amount of NH3 discharged from sewage sludge incineration facilities has not been calculated. Therefore, in this study, we sought to determine whether NH3 is discharged in the exhaust gas of a sewage sludge incineration facility, and, when discharged, the NH3 emission factor was calculated, and the necessity of the development of the emission factor was reviewed. As a result of the study, it was confirmed that the amount of NH3 discharged from the sewage sludge incineration facility was 0.04 to 4.47 ppm, and the emission factor was calculated as 0.002 kg NH3/ton. The NH3 emission factor was compared with the NH3 emission factor of municipal solid waste proposed by EMEP/EEA (European Monitoring and Evaluation Programme/European Environment Agency) because the NH3 emission factor of the sewage sludge incineration facility had not been previously determined. As a result of the comparison, the NH3 emission factor of EMEP/EEA was similar to that of municipal solid waste, confirming the necessity of developing the NH3 emission factor of the sewage sludge incineration facility. In addition, the evaluation of the uncertainty of the additionally calculated NH3 emission factor was conducted quantitatively and the uncertainty range was presented for reference. In the future, it is necessary to improve the reliability of the NH3 emission factor of sewage sludge incineration facilities by performing additional analysis with statistical representation. In addition, the development of NH3 emission factors for industrial waste incineration facilities should be undertaken.

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“…Out of these combustion sites, NH 3 emission volumes are calculated for plants for power generation and petroleum product production. The amount of NH 3 emitted through slip is estimated due to the operation of selective catalytic reductions (SCRs) and selective non-catalytic reductions (SNCRs) that utilize NH 3 to reduce NOx [10,11]. Moreover, SCRs and SNCRs are installed and operated in municipal waste combustion sites, but the resulting NH 3 emission amounts are currently not calculated in Korea.…”

Section: Introductionmentioning

confidence: 99%

Ammonia Emission Characteristics and Emission Factor of Municipal Solid Waste Incineration Plant

2020

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This study aims to analyze whether ammonia emission occurs when municipal solid waste (MSW) is incinerated. In cases where ammonia is emitted, we aim to develop an emission factor, calculate annual emission amounts by utilizing activity data (waste incineration amount) applied in air pollutant emission calculations for the waste combustion in Korea, and investigate whether there is a need for emission calculation. As a result of the study, the ammonia emission factor of the MSW incineration facility to be studied was 0.0091 kgNH3/ton, which was 3 times higher than the emission factor in Europe. In the case of emissions, a randomly developed emission factor was applied to confirm the necessity of development of the emission factor, and as a result of the application, it was found to be 22 NH3 ton/year, which is the same number as the annual NH3 emission of the entire waste treatment sector in 2016. Therefore, we believe that MSW incinerator facilities should be recognized as one of the major NH3 omitted emission sources. Moreover, it is evident that there is a need for an NH3 emission factor and emission calculations that reflect the characteristics of Korea.

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Modeling and Multi-Objective Optimization of NOx Conversion Efficiency and NH3 Slip for a Diesel Engine

Cited by 22 publications

References 34 publications

Automotive IVHM: Towards Intelligent Personalised Systems Healthcare

Automotive IVHM: Towards Intelligent Personalised Systems Healthcare

Estimating the Characteristics and Emission Factor of Ammonia from Sewage Sludge Incinerator

Ammonia Emission Characteristics and Emission Factor of Municipal Solid Waste Incineration Plant

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