Air flowrate and particle size effect on gasification of arecanut husk with preheated air through waste heat recovery from syngas

Vikraman, V. Karuppasamy; Subramanian, P.; Kumar, D. Praveen; Sriramajayam, S.; Mahendiran, R.; Ganapathy, Suthakar

doi:10.1016/j.biteb.2022.100977

Cited by 6 publications

(2 citation statements)

References 27 publications

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“…39 The Air flowrate was found to have a superior impact on gasification characteristics. 40 The literature has reported a low air mass flow rate of 4.33 kg h −1 in the case of gasification of a combination consisting of coal and coconut shell. Furthermore, an increase in the air mass flow rate advocates more heat generation.…”

Section: Resultsmentioning

confidence: 99%

An experimental and response-surface-based optimization approach towards production of producer gas in a circulating fluidized bed gasifier using blends of renewable fibre-based biomass mixtures

Viswakethu,

Pichappan,

Perumal

et al. 2024

Sustainable Energy Fuels

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Section: Resultsmentioning

confidence: 99%

An experimental and response-surface-based optimization approach towards production of producer gas in a circulating fluidized bed gasifier using blends of renewable fibre-based biomass mixtures

Viswakethu,

Pichappan,

Perumal

et al. 2024

Sustainable Energy Fuels

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“…Of the reviewed studies that applied data-driven methods to model RRCC technologies, 20% (36% statistical and 64% ML methods) represented models that predicted syngas yield through the gasification of various feedstocks (Figure a and Table S9). Gasification was most frequently modeled by applying MPR ,− using primary data and ANN ,− using both primary and secondary data. These MPR and ANN models respectively, comprised 33% and 36% of the data-driven gasification models (Figure a and Table S9).…”

Section: Applications Of Data Science In Rrcc From Organic Waste Streamsmentioning

confidence: 99%

A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste

Zaki,

Rowles,

Adjeroh

et al. 2023

ACS EST Eng.

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Municipal and agricultural organic waste can be treated to recover energy, nutrients, and carbon through resource recovery and carbon capture (RRCC) technologies such as anaerobic digestion, struvite precipitation, and pyrolysis. Data science could benefit such technologies by improving their efficiency through data-driven process modeling along with reducing environmental and economic burdens via life cycle assessment (LCA) and techno-economic analysis (TEA), respectively. We critically reviewed 616 peer-reviewed articles on the use of data science in RRCC published during 2002−2022. Although applications of machine learning (ML) methods have drastically increased over time for modeling RRCC technologies, the reviewed studies exhibited significant knowledge gaps at various model development stages. In terms of sustainability, an increasing number of studies included LCA with TEA to quantify both environmental and economic impacts of RRCC. Integration of ML methods with LCA and TEA has the potential to costeffectively investigate the trade-off between efficiency and sustainability of RRCC, although the literature lacked such integration of techniques. Therefore, we propose an integrated data science framework to inform efficient and sustainable RRCC from organic waste based on the review. Overall, the findings from this review can inform practitioners about the effective utilization of various data science methods for real-world implementation of RRCC technologies.

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Essential oil distillation residue as environmentally friendly feedstock in gasification: effect of dry air flow rate and temperature on gasification performance

Yılmaz Çinçin,

Öngen,

Ağdağ

2024

Biomass Conv. Bioref.

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Despite the growing use of distillation to extract essential oils from aromatic plants, their residues pose a challenge due to their high cellulose-lignin content and resistance to biodegradation, requiring thermochemical treatment for removal. This paper presents the effect of flow rate of agent and operation temperature on the gasification of Oregano (Origanum onites L.) and Lavender (Lavandula angustifolia) distillation residue in an updraft fixed bed reactor. The syngas composition, lower heating value of syngas, carbon conversion efficiency, cold gas efficiency, and amount of product are assessed during gasification process. In the experimental studies, a laboratory-scale upstream fixed-bed gasification reactor made of stainless steel heated with a ceramic heater resistant was used. The studies were carried out at temperatures of 700, 800, and 900 °C and a dry air flow rate of 0.05–0.4 L/min to find optimum conditions for gasification. Results showed that increasing the temperature and reducing the dry air flow rate led to higher syngas production and heating value. The maximum volume of H2 in the syngas was measured as 40%. The HHV varied between 5 and 13 MJ/Nm3. The optimum flow rate and temperature for gasification in the updraft fixed bed reactor were found to be 0.05–0.1 L/min and 900 °C, respectively. Graphical Abstract

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Air flowrate and particle size effect on gasification of arecanut husk with preheated air through waste heat recovery from syngas

Cited by 6 publications

References 27 publications

An experimental and response-surface-based optimization approach towards production of producer gas in a circulating fluidized bed gasifier using blends of renewable fibre-based biomass mixtures

An experimental and response-surface-based optimization approach towards production of producer gas in a circulating fluidized bed gasifier using blends of renewable fibre-based biomass mixtures

A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste

Essential oil distillation residue as environmentally friendly feedstock in gasification: effect of dry air flow rate and temperature on gasification performance

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