Vision based algorithm for automated determination of smoke point of diesel blends

Rubio-Gomez, Guilllermo; Corral-Gómez, Lis; Soriano, José A.; Gómez, Arántzazu; Castillo-García, Fernando J.

doi:10.1016/j.fuel.2018.08.032

Cited by 16 publications

(11 citation statements)

References 19 publications

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“…Laminar diffusion flames are of particular interest because they allow the controlled investigation of the chemistry occurring in fuel-rich regions, which is relevant to full-scale practical combustion devices such as gas turbines, furnaces and internal combustion engines [35]. Initial work in this direction has investigated the sooting behaviour of liquid fuels using a smoke point lamp [36,37,38,39,40,41,42], including investigation of the sooting propensity of PODE n -diesel blends using a smoke point lamp [43]. The dilution of the fuel with the PODE n was shown to have an important effect on the reduction of the soot in addition to the oxygen content of the PODE n .…”

mentioning

confidence: 99%

The effect of poly(oxymethylene) dimethyl ethers (PODE3) on soot formation in ethylene/PODE3 laminar coflow diffusion flames

Tan

Salamanca

Pascazio

et al. 2021

Fuel

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mentioning

confidence: 99%

The effect of poly(oxymethylene) dimethyl ethers (PODE3) on soot formation in ethylene/PODE3 laminar coflow diffusion flames

Tan

Salamanca

Pascazio

et al. 2021

Fuel

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“…The Threshold Sooting Index (TSI) enables a comparison of the sooting tendency of different hydrocarbon fuel blends on a unified scale that is independent of the SP apparatus [84][85][86][87][88][89][90]. The TSI provides an experimentallyobtained correlation with the SP [83] that is directly proportional to the molecular weight (MW) and inversely proportional to the SP of the fuel [91].…”

Section: Smoke Point and Sooting Indicesmentioning

confidence: 99%

How do the oxygenated functional groups in ether, carbonate and alcohol affect soot formation in Jet A2 diffusion flames?

Tan

Salamanca

Akroyd

et al. 2022

Combustion and Flame

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“…The implementation of microcontrollers can deliver a cost-effective and trouble-free solution for such aims with high benefits on the other side. Such a solution can also be found in recent literature in various fields of research [1][2][3][4][5][6]. Although many incentives have been completed to apply control solutions based on Arduino, it has not been introduced into chemical engineering and chemical engineering research [7,8].…”

Section: Introductionmentioning

confidence: 99%

Low-Cost and Efficient Solution for the Automation of Laboratory Scale Experiments: The Case of Distillation Column

et al. 2022

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Chemical laboratories badly need efficient support for human works when experiments are carried out. Process control and data acquisition at the laboratory scale are still practical challenges among others, due to equipment prices and the relative complexity of the different scientific disciplines. There is, however, a large demand recently for the so-called Internet of Things (IoT), intelligent/smart labeled solutions that also include laboratory equipment items. Such solutions have enormous potential in making research activity and routine laboratory work efficient and easy by implementing proper data acquisition and control for laboratory-scale equipment items. To solve these practical challenges, an efficient and simple solution was designed and completed for the control and data acquisition of a laboratory-scale rectification process by a well-known microcontroller connected to MATLAB/Simulink. The straightforward application of this solution is demonstrated in case study measurements. The data acquired were used also for process identification. The data were then further processed for various simple and more advanced tunings that were applied, evaluated, and compared. By implementing gain scheduling, significant improvements can be achieved compared to model-based PID tunings while the application of self-tuning by adaptive interaction demands too much consideration for better evaluation with low benefit. Furthermore, the developed device introduces the advantages of digitalization and the 4.0 industrial revolution in the laboratory as well as supports human laboratory work. It also narrows the gap between the laboratory and industrial environment items since the final design can provide a complete process control experience already at the laboratory scale.

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Vision based algorithm for automated determination of smoke point of diesel blends

Cited by 16 publications

References 19 publications

The effect of poly(oxymethylene) dimethyl ethers (PODE3) on soot formation in ethylene/PODE3 laminar coflow diffusion flames

The effect of poly(oxymethylene) dimethyl ethers (PODE3) on soot formation in ethylene/PODE3 laminar coflow diffusion flames

How do the oxygenated functional groups in ether, carbonate and alcohol affect soot formation in Jet A2 diffusion flames?

Low-Cost and Efficient Solution for the Automation of Laboratory Scale Experiments: The Case of Distillation Column

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