Modeling the Biogas and Methane Yield from Anaerobic Digestion of Arachis hypogea Shells with Combined Pretreatment Techniques Using Machine Learning Approaches

Olatunji, Kehinde O.; Madyira, Daniel M.; Ahmed, Noor A.; Adeleke, Oluwatobi; Ogunkunle, Oyetola

doi:10.1007/s12649-022-01935-2

Cited by 13 publications

(6 citation statements)

References 64 publications

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“…This shows that the model provides an accuracy of 91% in predicting the methane released from Xyris capensis pretreated with oxidizing agents. This value is lower than what some authors reported [4] but higher than what was observed by other authors in related studies [19]. R 2 within the range of 0.75 and 1 has been adjudged to be an excellent predictive ability of a model [12], this shows that the result from this study is satisfactory.…”

Section: Resultscontrasting

confidence: 47%

Application of response surface methodology (RSM) for optimizing methane yield of oxidative pretreated Xyris capensis

Olatunji,

Madyira

2023

E3S Web Conf.

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This study investigated the application of Response Surface Methodology (RSM) for optimizing and predicting methane yield from oxidative pretreated Xyris capensis. Input process parameters of retention time, temperature, and pretreatment condition were considered, with methane yield as the response. The results show that all three process parameters selected significantly influence methane yield, and analysis of variance (ANOVA) indicates that the RSM model is significant for the study. A correlation coefficient (R2) of 0.9071 was recorded, which implies that the model has 91% prediction accuracy. Interactive influence of temperature and retention time, pretreatment and retention time, and pretreatment and temperature were significant to methane release. Optimum conditions for methane release from RSM model are 14 days retention time, 25 °C temperature, and pretreatment condition of 85% H2O2 and 15% H2SO4 with daily optimum methane yield of 32.65 mLCH4 /gVSadded. This study shows that RSM is suitable for methane yield optimization and prediction during the anaerobic digestion of oxidative pretreated lignocellulose substrates.

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Section: Resultscontrasting

confidence: 47%

Application of response surface methodology (RSM) for optimizing methane yield of oxidative pretreated Xyris capensis

Olatunji,

Madyira

2023

E3S Web Conf.

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“…These models do not give directly mechanistic explanation of the simulated phenomena, which, at least, is not the prioritized purpose of these models. The machine leaning approach (including artificial neural network, ANN) has been largely studied to predict the performance of wastewater treatment plant [94], the process of upflow anaerobic sludge blanket process (UASB) [95], the LSAD of sewage sludge [96], industrial sludge [97] and agricultural byproducts [98].…”

Section: Advanced Statistical Modelsmentioning

confidence: 99%

Overview of Numerical Simulation of Solid-State Anaerobic Digestion Considering Hydrodynamic Behaviors, Phenomena of Transfer, Biochemical Kinetics and Statistical Approaches

Liu

Coutu²,

Mottelet

et al. 2023

Energies

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Anaerobic digestion (AD) is a promising way to produce renewable energy. The solid-state anaerobic digestion (SSAD) with a dry matter content more than 15% in the reactors is seeing its increasing potential in biogas plant deployment. The relevant processes involve multiple of evolving chemical and physical phenomena that are not crucial to conventional liquid-state anaerobic digestion processes (LSAD). A good simulation of SSAD is of great importance to better control and operate the reactors. The modeling of SSAD reactors could be realized either by theoretical or statistical approaches. Both have been studied to a certain extent but are still not sound. This paper introduces the existing mathematical tools for SSAD simulation using theoretical, empirical and advanced statistical approaches and gives a critical review on each type of model. The issues of parameter identifiability, preference of modeling approaches, multiscale simulations, sensibility analysis, particularity of SSAD operations and global lack of knowledge in SSAD media evolution were discussed. The authors call for a stronger collaboration of multidisciplinary research in order to further developing the numeric simulation tools for SSAD.

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“…102 The main demerit of mechanical pretreatment is that it needs high energy consumption, which may make the process not economical. 103 Mechanical pretreatment employed different means to break the recalcitrance characteristics of the macroalgae and improve the biogas and methane yield. Milling or grinding can be used to enhance the crystallinity of the macroalgae.…”

Section: Macroalgae Pretreatmentmentioning

confidence: 99%

Sustainable enhancement of biogas and methane yield of macroalgae biomass using different pretreatment techniques: A mini-review

Olatunji

Madyira

Amos

2023

Energy & Environment

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Macroalgae can be grown without the use of fertilizer, fresh water, or arable land. These qualities support its use for biofuel production because it frees up land for other traditional energy sources and food crops. It has been investigated as biogas feedstock to substitute for fossil fuels burning with attendant effects on the ecosystem. The microstructural arrangement of macroalgae biomass is restricting their conversion to biogas. Therefore, application of pretreatment before anaerobic digestion is needed to enhance their availability to microbial degradation and subsequent increase in biogas yield. Pretreatment application for substrate catalysis is vital to recovering eco-friendly and economical energy from macroalgae. This study summarizes the state of the art of various pretreatment methods employed to enhance macroalgae biomass's anaerobic digestion process. These methods were categorized as thermal, biological, chemical, nanoparticle additives, mechanical, and combined. Merits and challenges associated with each of these methods were also considered. The study shows that all the pretreatment methods considered can improve the biogas yield if the appropriate method is selected based on the type of macroalgae species. Pilot-scale studies that will assist in assessing their feasibility on the full-scale implementation are still missing.

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Modeling the Biogas and Methane Yield from Anaerobic Digestion of Arachis hypogea Shells with Combined Pretreatment Techniques Using Machine Learning Approaches

Cited by 13 publications

References 64 publications

Application of response surface methodology (RSM) for optimizing methane yield of oxidative pretreated Xyris capensis

Application of response surface methodology (RSM) for optimizing methane yield of oxidative pretreated Xyris capensis

Overview of Numerical Simulation of Solid-State Anaerobic Digestion Considering Hydrodynamic Behaviors, Phenomena of Transfer, Biochemical Kinetics and Statistical Approaches

Sustainable enhancement of biogas and methane yield of macroalgae biomass using different pretreatment techniques: A mini-review

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