An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype

Adeyemi Kudirat Olubukola; Boyo Henry Oritsemamididasan

doi:doi:10.11648/j.cbb.20221001.11

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An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype

Adeyemi Kudirat Olubukola, Boyo Henry Oritsemamididasan

Published in Computational Biology and Bioinformatics (Volume 10, Issue 1)

Received: 20 November 2021 Accepted: 22 December 2021 Published: 29 March 2022

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Abstract

Experiments were carried out to determine the relationship between density of liquid (pure water) and compression of five springs supporting a 1000 Liter tank from beneath. The tank is meant to be an anaerobic digester for production of biogas. The springs constant were determined and were used to compute the densities of a fixed concentration of two unknown liquids (that of a fixed concentration of salt and the other had varying concentration). Results show that each of the five springs had different spring constants ranging from 62,177N/m or Kg/s.s to 167,048N/m or Kg/s.s. The average density of the liquid with fixed concentration of salt is 1118.24Kg/cu.m which compares excellently well with the density of pure water (1000Kg/cu.m). The unknown liquid with varying concentration of salt follows an exponential relationship Y=3E-05e^42.67x and a correlation of 0.97, where Y stands for density of the fluid and X the corresponding extension of the spring. We have used the expression to predict the density of similar water of unknown concentration. Since methane gas production potential depends on water dilution ratio, it is expected that we can calibrate any digester tank to give direct readings of densities of bio-degradable material from mere displacement of the suspension springs.

Published in	Computational Biology and Bioinformatics (Volume 10, Issue 1)
DOI	10.11648/j.cbb.20221001.11
Page(s)	1-8
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Anaerobic, Bio-degradable, Biogas, Correlation, Density, Methane Gas

References

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[2]	G. Caposciutti, A. Baccioli, L. Ferrari, and U. Desideri, “Biogas from anaerobic digestion: power generation or biomethane production?” Energies, vol. 13, no. 3, 2020.
[3]	O. W. Awe, Y. Zhao, A. Nzihou, D. P. Minh, and N. Lyczko, “A review of biogas utilization, purification and upgrading technologies, ”Waste and Biomass Valorization, vol. 8, no. 2, pp. 267-283, 2017.
[4]	Punal A., Lorenzo A., Roca E., Hernandez C., Lema J. M. (1999). Advanced monitoring of an anaerobic pilot plant treating high strength waste waters. Water SciTechnol 40: 237-244.
[5]	Fischer, G. and Schrattenholzer, L. (2001). Global Bioenergy Potential through 2050. Biomass and Bioenergy. 20 (3): 151-159.
[6]	Berndes G, Hoogwijk M. Broek R. (2003). The contribution of biomass in the future global energy supply: a review of 17 studies. (01) 29.
[7]	V. Vojinovic, J. M. S. Cabral, L. P. Fonseca (2006). Review Real-time bioprocess monitoring. Part 1: In situ sensors – INFONA – science.
[8]	Kristiina K., Kalle S., Ulla M., Tero E. (2008). The performance of in situ measurements and software sensors. Industrial Microbiology and Biotechnology. 35: 657-665.
[9]	Lakshmi P., Reddy M. S., Reddy C. P., Rao A. N. (2016). Studies of Physico-Chemical Parameters. Earth Sci Clim Change. 7: 347.
[10]	Karl Schugerl (2001). Progress in monitoring, modeling and control of bioprocesses during the last 20 years. Journal of Biotechnology. 85: 149-173.
[11]	Scarff M., Arnold S. A., Harvey L. M., McNeil B. (2006). Near infrared spectroscopy for bioprocess monitoring and control: current status and future trends. Crit Rev Biotechnol 26: 17-39.
[12]	Bellon-Maurel V., Orliac O., Christen P. (2003) Sensors and measurements in solid state fermentation: a review. Process Biochem 38: 881-896.
[13]	Holm-Neilsen, Kim H. Esbensen (2008). Process Analytical Technologies for Anaerobic Digestion Systems. researchgate.net.
[14]	Yansheng Zhang, Takaaki Maekawa (2002). Monitoring of methanogen density using near- infrared spectroscopy. Biomass and Bioenergy. Vol. 22, no 6: 489-495.
[15]	Endress+Hauser, Automation and process control in biogas production.

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APA Style

Adeyemi Kudirat Olubukola, Boyo Henry Oritsemamididasan. (2022). An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype. Computational Biology and Bioinformatics, 10(1), 1-8. https://doi.org/10.11648/j.cbb.20221001.11

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ACS Style

Adeyemi Kudirat Olubukola; Boyo Henry Oritsemamididasan. An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype. Comput. Biol. Bioinform. 2022, 10(1), 1-8. doi: 10.11648/j.cbb.20221001.11

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AMA Style

Adeyemi Kudirat Olubukola, Boyo Henry Oritsemamididasan. An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype. Comput Biol Bioinform. 2022;10(1):1-8. doi: 10.11648/j.cbb.20221001.11

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@article{10.11648/j.cbb.20221001.11,
  author = {Adeyemi Kudirat Olubukola and Boyo Henry Oritsemamididasan},
  title = {An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype},
  journal = {Computational Biology and Bioinformatics},
  volume = {10},
  number = {1},
  pages = {1-8},
  doi = {10.11648/j.cbb.20221001.11},
  url = {https://doi.org/10.11648/j.cbb.20221001.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20221001.11},
  abstract = {Experiments were carried out to determine the relationship between density of liquid (pure water) and compression of five springs supporting a 1000 Liter tank from beneath. The tank is meant to be an anaerobic digester for production of biogas. The springs constant were determined and were used to compute the densities of a fixed concentration of two unknown liquids (that of a fixed concentration of salt and the other had varying concentration). Results show that each of the five springs had different spring constants ranging from 62,177N/m or Kg/s.s to 167,048N/m or Kg/s.s. The average density of the liquid with fixed concentration of salt is 1118.24Kg/cu.m which compares excellently well with the density of pure water (1000Kg/cu.m). The unknown liquid with varying concentration of salt follows an exponential relationship Y=3E-05e42.67x and a correlation of 0.97, where Y stands for density of the fluid and X the corresponding extension of the spring. We have used the expression to predict the density of similar water of unknown concentration. Since methane gas production potential depends on water dilution ratio, it is expected that we can calibrate any digester tank to give direct readings of densities of bio-degradable material from mere displacement of the suspension springs.},
 year = {2022}
}

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TY  - JOUR
T1  - An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype
AU  - Adeyemi Kudirat Olubukola
AU  - Boyo Henry Oritsemamididasan
Y1  - 2022/03/29
PY  - 2022
N1  - https://doi.org/10.11648/j.cbb.20221001.11
DO  - 10.11648/j.cbb.20221001.11
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 1
EP  - 8
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20221001.11
AB  - Experiments were carried out to determine the relationship between density of liquid (pure water) and compression of five springs supporting a 1000 Liter tank from beneath. The tank is meant to be an anaerobic digester for production of biogas. The springs constant were determined and were used to compute the densities of a fixed concentration of two unknown liquids (that of a fixed concentration of salt and the other had varying concentration). Results show that each of the five springs had different spring constants ranging from 62,177N/m or Kg/s.s to 167,048N/m or Kg/s.s. The average density of the liquid with fixed concentration of salt is 1118.24Kg/cu.m which compares excellently well with the density of pure water (1000Kg/cu.m). The unknown liquid with varying concentration of salt follows an exponential relationship Y=3E-05e42.67x and a correlation of 0.97, where Y stands for density of the fluid and X the corresponding extension of the spring. We have used the expression to predict the density of similar water of unknown concentration. Since methane gas production potential depends on water dilution ratio, it is expected that we can calibrate any digester tank to give direct readings of densities of bio-degradable material from mere displacement of the suspension springs.
VL  - 10
IS  - 1
ER  -

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Author Information

Adeyemi Kudirat Olubukola

Physics Department, Rivers State University, Port-Harcourt, Nigeria
Boyo Henry Oritsemamididasan

Physics Department, Elizade University, Ilara-Mokin, Nigeria

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APA Style

Adeyemi Kudirat Olubukola, Boyo Henry Oritsemamididasan. (2022). An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype. Computational Biology and Bioinformatics, 10(1), 1-8. https://doi.org/10.11648/j.cbb.20221001.11

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ACS Style

Adeyemi Kudirat Olubukola; Boyo Henry Oritsemamididasan. An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype. Comput. Biol. Bioinform. 2022, 10(1), 1-8. doi: 10.11648/j.cbb.20221001.11

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AMA Style

Adeyemi Kudirat Olubukola, Boyo Henry Oritsemamididasan. An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype. Comput Biol Bioinform. 2022;10(1):1-8. doi: 10.11648/j.cbb.20221001.11

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@article{10.11648/j.cbb.20221001.11,
  author = {Adeyemi Kudirat Olubukola and Boyo Henry Oritsemamididasan},
  title = {An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype},
  journal = {Computational Biology and Bioinformatics},
  volume = {10},
  number = {1},
  pages = {1-8},
  doi = {10.11648/j.cbb.20221001.11},
  url = {https://doi.org/10.11648/j.cbb.20221001.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20221001.11},
  abstract = {Experiments were carried out to determine the relationship between density of liquid (pure water) and compression of five springs supporting a 1000 Liter tank from beneath. The tank is meant to be an anaerobic digester for production of biogas. The springs constant were determined and were used to compute the densities of a fixed concentration of two unknown liquids (that of a fixed concentration of salt and the other had varying concentration). Results show that each of the five springs had different spring constants ranging from 62,177N/m or Kg/s.s to 167,048N/m or Kg/s.s. The average density of the liquid with fixed concentration of salt is 1118.24Kg/cu.m which compares excellently well with the density of pure water (1000Kg/cu.m). The unknown liquid with varying concentration of salt follows an exponential relationship Y=3E-05e42.67x and a correlation of 0.97, where Y stands for density of the fluid and X the corresponding extension of the spring. We have used the expression to predict the density of similar water of unknown concentration. Since methane gas production potential depends on water dilution ratio, it is expected that we can calibrate any digester tank to give direct readings of densities of bio-degradable material from mere displacement of the suspension springs.},
 year = {2022}
}

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TY  - JOUR
T1  - An Automated Process to Compute Density of Unknown Liquid (Organic Slurry) Using Brine as a Prototype
AU  - Adeyemi Kudirat Olubukola
AU  - Boyo Henry Oritsemamididasan
Y1  - 2022/03/29
PY  - 2022
N1  - https://doi.org/10.11648/j.cbb.20221001.11
DO  - 10.11648/j.cbb.20221001.11
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 1
EP  - 8
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20221001.11
AB  - Experiments were carried out to determine the relationship between density of liquid (pure water) and compression of five springs supporting a 1000 Liter tank from beneath. The tank is meant to be an anaerobic digester for production of biogas. The springs constant were determined and were used to compute the densities of a fixed concentration of two unknown liquids (that of a fixed concentration of salt and the other had varying concentration). Results show that each of the five springs had different spring constants ranging from 62,177N/m or Kg/s.s to 167,048N/m or Kg/s.s. The average density of the liquid with fixed concentration of salt is 1118.24Kg/cu.m which compares excellently well with the density of pure water (1000Kg/cu.m). The unknown liquid with varying concentration of salt follows an exponential relationship Y=3E-05e42.67x and a correlation of 0.97, where Y stands for density of the fluid and X the corresponding extension of the spring. We have used the expression to predict the density of similar water of unknown concentration. Since methane gas production potential depends on water dilution ratio, it is expected that we can calibrate any digester tank to give direct readings of densities of bio-degradable material from mere displacement of the suspension springs.
VL  - 10
IS  - 1
ER  -

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