Mechanism of molasses–water mixing behavior in bioethanol fermenter. Experiments and CFD modeling

Madhania, Suci; Muharam, Yuswan; Winardi, Sugeng; Purwanto, Widodo Wahyu

doi:10.1016/j.egyr.2019.04.008

Cited by 16 publications

(10 citation statements)

References 28 publications

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“…The latter should be tested for different experimental setups (e.g., water-unsaturated soils, LNAPL compounds, saltwater intrusion), other non-consolidated porous media (e.g., silty sand, clay lenses, combinations of several sediment fractions), and fractured rock (e.g., sandstone, limestone) in order to point out the flexibility and transferability of the IPA framework presented here. [34,49,80] [ 56,62,66,68,76,78,79] Converting to gray scale [48] [ 82,83] Correction of spatially non-uniform illumination Correction using a reference image, either flat-field image or without tracer and then dividing, subtracting or normalizing to the image - [62,84,85] Converting by using adaptive thresholding algorithm using percent distance between peaks…”

Section: Limitations and Outlookmentioning

confidence: 99%

Quantification of Uncertainties from Image Processing and Analysis in Laboratory-Scale DNAPL Release Studies Evaluated by Reflective Optical Imaging

Engelmann

Schmidt

Werth

et al. 2019

Water

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Subsurface DNAPL (dense non-aqueous phase liquid) contamination from (un-) intentional spilling typically leads to severe environmental hazards. A large number of studies have demonstrated the relevance of DNAPL source zone geometry for the determination of contaminant plume propagation in groundwater. Optical imaging represents a promising non-invasive method for identifying DNAPL saturation without disturbing multiphase flow dynamics. However, workflow and image analysis methodologies have not been sufficiently developed or described for general application to related experimental efforts. For example, the choice of dye(s) used for phase colorization affects image processing and can bias final estimations of DNAPL saturations. In this study, we perform a series of DNAPL migration and entrapment studies in transparent tanks that are filled with three different types of porous media. Different dyes are used and raw images are acquired. Subsequently, these are used to evaluate a suite of image processing and analysis approaches, which are organized into a workflow. Our approach allows for us to identify key image processing and analysis steps that introduce the most error. Applicable dye configurations led to uncertainties of up to 41% depending on the selection of processing steps. Based on these findings, it was possible to delineate a flexible framework for image processing and analysis that has the potential for transfer and application in other tank experiment setups.

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Section: Limitations and Outlookmentioning

confidence: 99%

Quantification of Uncertainties from Image Processing and Analysis in Laboratory-Scale DNAPL Release Studies Evaluated by Reflective Optical Imaging

Engelmann

Schmidt

Werth

et al. 2019

Water

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“…Many researchers have conducted research to improve mixing efficiency in stirred tanks. Based on the studies that have been carried out, the effectiveness of the mixing process in a stirred tank is influenced by, among others, tank design includes the position of the stirrer installation (Madhania et al, 2017), the existence of baffles (Pukkella et al, 2019), the type of stirrer (Sossa-Echeverria and Taghipour, 2015;Reviol et al, 2018), the working fluid (Madhania et al, 2019b) and stirrer rotational speed (Madhania et al, 2019a).…”

Section: Introductionmentioning

confidence: 99%

Turbulence Modeling in Side-Entry Stirred Tank Mixing Time Determination

et al. 2021

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Mixing is one of the critical processes in the industry. The stirred tank is one of the operating units commonly used in the mixing process. Several factors greatly influence the efficiency of the stirred tank, including the stirred-tank design, operating conditions, and working fluid properties. The side-entry stirred tank is widely applied in industry, among others; the processing of crude oil in the refinery industry, water-molasses mixing in the bioethanol industry, pulp stock chest in the pulp and paper industry, and anaerobic digester for biogas reactors. Mixing time is one of the critical parameters used in the design of the stirred tank. This research will model mixing time in a flat bottomed-cylindrical side-entry stirred tank with dimensions D = 40 cm and T = 40 cm using CFD ANSYS 18.2 by applying the Standard κ − ε (SKE) and Realizable κ − ε (RKE) turbulence models. The stirrer used is a three-blade marine propeller d = 4 cm which is an axial type impeller. The phenomenon of mixing in the side-entry stirred tank, qualitatively described through computational prediction results in the form of flow profiles and tracer density change contours locally. Moreover, quantitatively indicated by mixing time validated using experimental data carried out by the conductometry method. The computational prediction shows that the mixing time modeled using the SKE turbulence model shows a similarity level of 68.16%, while the RKE turbulence model shows 31.94%.

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“…Fossil fuel based energy sources are being increasingly depleted (Madhania et al, 2019) and the demand for renewable energy is steadily increasing due to rapid population growth and economic development worldwide (Mujtaba et al, 2020). Nowadays there are many renewable energy resources to replace fossil fuels such as: Hydropower, wind, solar, geothermal and biofuels (Weida et al, 2016;Alemán-Nava et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A Bibliometric Analysis of Sugar Beet for Production of Biofuels

Jiménez-Islas

Pérez-Romero

Ríos-Rivera

et al. 2021

IJEEP

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The ongoing depletion of fossil resources, the energetic autonomy of countries, soaring prices for petroleum and climate change have stimulated research and development on renewable energy as biofuels. In this work, a bibliometric analysis of the Web of Science database was carried out to identify the research related to sugar beet to biofuels. The equation logistic was used to quantitatively describe the growth of the publication of sugar beet in the biofuels field. The results show that the publications of sugar beet for biofuel have a rate of growth of 0-1898 year −1 . Germany and the USA were the countries with high influence for research in the field of sugar beet for biofuels. The journal Zuckerindustrie was the referent to publications in the field of study. From 2003 to 2019, the exponential growth of publications was found, this profile of growth can be attributed to the development of renewable energy and the relevance of global warming, security energetic and laws that promoted clean energy. This work shows that the logistic equation can be used to predict the evolution of publications in the field of study.

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Mechanism of molasses–water mixing behavior in bioethanol fermenter. Experiments and CFD modeling

Cited by 16 publications

References 28 publications

Quantification of Uncertainties from Image Processing and Analysis in Laboratory-Scale DNAPL Release Studies Evaluated by Reflective Optical Imaging

Quantification of Uncertainties from Image Processing and Analysis in Laboratory-Scale DNAPL Release Studies Evaluated by Reflective Optical Imaging

Turbulence Modeling in Side-Entry Stirred Tank Mixing Time Determination

A Bibliometric Analysis of Sugar Beet for Production of Biofuels

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