Technical Papers
Sep 30, 2022

Probabilistic Design of Gas Collection Systems for a Prototype Bioreactor

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 4

Abstract

Prototype bioreactor studies are becoming an increasingly common approach to assessing municipal solid waste degradation in landfills, owing to their greater potential for monitoring and control. Though reports of several bioreactor studies have appeared in the literature, the performance of a laboratory-scale bioreactor in the presence of a gas collection system (GCS) has not been investigated anywhere. Because the properties of waste in a landfill or a bioreactor can vary temporally and spatially, it is essential to account for these variabilities while designing a GCS. In this study, a GCS for a prototype bioreactor was designed using kriging surrogate models to account for the variability in the waste properties. The numerical models required to calibrate the kriging models were implemented through TOUGH3 EOS7CA (three-dimensional simulations). The radius of influence (ROI) of a gas extraction well (a critical parameter that controls the design of a GCS) was estimated by selecting methane generation rate (MGR), suction pressure (Sp), absolute permeability (k), and depth of the extraction well (D) as the input parameters. The ROI and gas pressure distributions inside the bioreactor were determined accounting for the variabilities in the input parameters through Monte Carlo simulations on the kriging model. Gas pressures inside the prototype bioreactor with a single gas extraction well (GEW) system indicated that the bioreactor was unsafe—values far higher than atmospheric pressures were observed. A sensitivity analysis was conducted to achieve efficiency and optimize the design, revealing that Sp and MGR were the critical parameters that controlled the ROI. Hence, the GCS was designed with two GEWs, and the safety of the bioreactor was assessed by varying only the critical parameters with another developed kriging model. Observance of gas pressures in the range of atmospheric pressure indicated that the design was safe. A relation was developed between Sp and MGR, which will help enable a 90% methane recovery at the GEWs. The probability of failure of the prototype bioreactor in the presence of the developed relation was also estimated. The low probability of failure (1.23×104) indicated that the design was safe.

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Data Availability Statement

All data, models, and code generated or used during the study appear in the published article.

Acknowledgments

The study is a part of the research from the Imprint Project IMP/2019/000442, “Development of Methodologies for Rehabilitation of Municipal Solid Waste Dumpsites,” funded by the Science and Engineering Research Board, Government of India, which is gratefully acknowledged.

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Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8Issue 4December 2022

History

Received: Feb 2, 2022
Accepted: Jul 1, 2022
Published online: Sep 30, 2022
Published in print: Dec 1, 2022
Discussion open until: Feb 28, 2023

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Postdoctoral Fellow, Dept. of Civil Engineering, Indian Institute of Science, Bangalore, Karnataka 560012, India (corresponding author). ORCID: https://orcid.org/0000-0002-0170-6174. Email: [email protected]
Research Scholar, Dept. of Civil Engineering, Indian Institute of Science, Bangalore, Karnataka 560012, India. ORCID: https://orcid.org/0000-0002-2501-4068. Email: [email protected]
Research Scholar, Dept. of Electrical Communication Engineering, Indian Institute of Science, Bangalore, Karnataka 560012, India. ORCID: https://orcid.org/0000-0001-9929-5504. Email: [email protected]
G. L. Sivakumar Babu, F.ASCE [email protected]
Professor, Dept. of Civil Engineering, Indian Institute of Science, Bangalore, Karnataka 560012, India. Email: [email protected]

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Cited by

  • Rainfall-Induced Probability of Failure in Spatially Variable Soil Slopes and a Case Study of the Konkan Railway Slope Failure, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10.1061/AJRUA6.RUENG-1112, 10, 1, (2024).
  • Reliability and Risk Analysis in Geotechnical and Geoenvironmental Engineering, Indian Geotechnical Journal, 10.1007/s40098-024-00909-6, (2024).

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