Generation of producer gas using coconut shells and sugar cane bagasse in updraft gasifier

Venkatesh, G.; Reddy, P. Ramakrishna; Kotari, Sairam

doi:10.1016/j.matpr.2017.07.278

Cited by 10 publications

(3 citation statements)

References 7 publications

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“…Salah satu biomassa yang memiliki potensi untuk dimanfaatkan menjadi sebagai bahan bakar gasifikasi adalah limbah tempurung kelapa. Beberapa peneliti telah memanfaatkan tempurung kelapa untuk dikonversi menjadi gas dengan desain reaktor updraft, down draft dan fluidized bed [4], [5], [6] [7]. Hasil penelitian menunjukkan bahwa prosentase combustible gas yang dihasilkan dan H2/CO masih rendah.…”

Section: Pendahuluanunclassified

Pengaruh Thermal Wall Terhadap Karakteristik Hidrodinamika Dan Karakteristik Syngas Pada Dual Fluidized Bed Gasifier Berbabahan Bakar Tempurung Kelapa Dengan Simulasi Berbasis CPFD

Aklis

Rohmat

Saptoadi

2021

mesin

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Artikel ini membahas simulasi pengaruh temperatur dinding atau thermal wall atau (t.w) terhadap karakteristik hidrodinamika dan karakteristik syngas Dual fluidized bed gasifier (DFBG) dengan bahan bakar biomassa tempurung kelapa berbasis computational particle fluid dynamics (CPFD). Simulasi dilakukan dengan menggunakan software paket Barracuda VR 17.1.0. Uap dengan suhu 423 K dan tekanan 101325 Pa digunakan sebagai agen gasifikasi. Partikel yang digunakan berupa pasir silika dengan densitas 2650 kg/m 3 dan ukuran antara 180-600 μm. Ukuran tempurung kelapa 2-4 mm. Parameter operasi DFBG meliputi kecepatan uap di gasifier 1,5 m/s, kecepatan udara di riser sebesar 10 m/s, kecepatan udara di L-valve sebesar 1,57 m/s dan kecepatan uap di loop-seal sebesar 0,4 m/s dan 0,5 m/s. Grid yang digunakan sejumlah 129.024 dan simulasi menggunkan 3 variasi thermal wall (t.w) masing-masing sebesar 873 K, 973 K dan 1073 K. Dari hasil simulasi diketahui thermal wall berpengaruh terhadap karakteristik hidrodinamika yang dihasilkan simulasi dimana pada simulasi temperatur rendah (t.w = 873 K) sirkulasi material bed tampak mengalami penumpukan di riser bagian bawah, hal ini tidak terjadi pada sirkulasi material bed yang dihasilkan oleh simulasi dengan t.w =973 K dan 1073 K. Komposisi dan distribusi spesies gas hasil gasifikasi yang dihasilkan simulasi dengan t.w yang berbeda-beda menunjukkan kecenderungan yang sama, dimana masing-masing variasi menghasilkan gas dengan komposisi yang didominasi CO dan H2. Pengaruh temperatur dinding terlihat pada naiknya komposisi dan yield masing-masing spesies gas., dimana kompoisisi gas naik 5,78 % saat t.w dinaikkan dari 873 K menjadi 973 K dan naik 2,8 % saat t.w naik menjadi1073 K. Yield gas naik 20,4 % saat t.w naik dari 873 K menjadi 973 K, dan naik sebesar 17,5 % saat t.w berubah dari 973 K menjadi 1073 K.. Kata kunci: dual fluidized bed gasifier, tempurung kelapa, CPFD, syngas, thermal wall

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Section: Pendahuluanunclassified

Pengaruh Thermal Wall Terhadap Karakteristik Hidrodinamika Dan Karakteristik Syngas Pada Dual Fluidized Bed Gasifier Berbabahan Bakar Tempurung Kelapa Dengan Simulasi Berbasis CPFD

Aklis

Rohmat

Saptoadi

2021

mesin

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“…The gasification process is carried out by using above mentioned biomass materials, in which Coconut shells gives low gas production rate (1.4724m 3 /hr) and low gasification efficiency (46.96%) & Sugar cane bagasse material gives high gas production rate (1.5535m 3 /hr) and high gasification efficiency (52.86%) [13]. mathematical model by using the COMMENT code to predict the effect of various operating parameters such as equivalence ratio (ER) and feed gas temperature on the performance of an updraft gasifier HTAG (high-temperature air gasification) [14].…”

Section: Introductionmentioning

confidence: 99%

Bio-pellets Manufacture from Palm Fruit Skin as Renewable Alternative Fuels in Updraft Type Gasification Furnaces

Abdurrahman¹,

Syafitri²,

Ridwan³

et al. 2020

IJDNE

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Biomass is a suitable alternative to be used as fuel, but the use of biomass without prior processing can cause respiratory disease. In Indragiri Hilir Regency, the utilization of palm fruit skin waste is still minimal. Bio-pellet is a fuel derived from biomass waste that has gone through a densification process. The process of making bio-pellets is carried out by refining the raw materials, mixing the adhesives, printing the raw materials that are pressed under high pressure, and drying. The results of the research on the bio-pellet characteristic test of Nipah fruit peel waste according to its parameters obtained an average value of 1.28% water content, 0.51% ash content, 21.3% flying substance content, 76.88% bound carbon content and weight. type 1.41 gr / cm3. For the combustion test in the updraft type gasification furnace with the addition of 0.5kg, 0.3kg and 0.2kg of fuel, the results obtained from the rate of fuel consumption are 0.041kg / minute, 0.033kg / minute and 0.033kg respectively. /minute. In the results of combustion efficiency, the value according to SNI 7926: 2013 is the addition of 0.5kg of fuel at the beginning of ignition and 0.2 kg at the end of ignition, which is 0.04.

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“…Venkatesh et al [15] employed different biomass feedstocks, including coconut shells, ground nutshells, sugar cane bagasse, and rice husks in an updraft gasifier. From the experimental study with a 1 h operating time for each feedstock, the temperatures for the zones of combustion, reduction, pyrolysis, and drying were 750 • C, 420 • C, 250 • C, and 180 • C, respectively.…”

mentioning

confidence: 99%

Applying Artificial Intelligence to Predict the Composition of Syngas Using Rice Husks: A Comparison of Artificial Neural Networks and Gradient Boosting Regression

Wen

Phuc

2021

Energies

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The purpose of this study is to utilize two artificial intelligence (AI) models to predict the syngas composition of a fixed bed updraft gasifier for the gasification of rice husks. Air and steam-air mixtures are the gasifying agents. In the present work, the feeding rate of rice husks is kept constant, while the air and steam flow rates vary in each case. The consideration of various operating conditions provides a clear comparison between air and steam-air gasification. The effects of the reactor temperature, steam-air flow rate, and the ratio of steam to biomass are investigated here. The concentrations of combustible gases such as hydrogen, carbon monoxide, and methane in syngas are increased when using the steam-air mixture. Two AI models, namely artificial neural network (ANN) and gradient boosting regression (GBR), are applied to predict the syngas compositions using the experimental data. A total of 74 sets of data are analyzed. The compositions of five gases (CO, CO2, H2, CH4, and N2) are predicted by the ANN and GBR models. The coefficients of determination (R2) range from 0.80 to 0.89 for the ANN model, while the value of R2 ranges from 0.81 to 0.93 for GBR model. In this study, the GBR model outperforms the ANNs model based on its ensemble technique that uses multiple weak learners. As a result, the GBR model is more convincing in the prediction of syngas composition than the ANN model considered in this research.

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Generation of producer gas using coconut shells and sugar cane bagasse in updraft gasifier

Cited by 10 publications

References 7 publications

Pengaruh Thermal Wall Terhadap Karakteristik Hidrodinamika Dan Karakteristik Syngas Pada Dual Fluidized Bed Gasifier Berbabahan Bakar Tempurung Kelapa Dengan Simulasi Berbasis CPFD

Pengaruh Thermal Wall Terhadap Karakteristik Hidrodinamika Dan Karakteristik Syngas Pada Dual Fluidized Bed Gasifier Berbabahan Bakar Tempurung Kelapa Dengan Simulasi Berbasis CPFD

Bio-pellets Manufacture from Palm Fruit Skin as Renewable Alternative Fuels in Updraft Type Gasification Furnaces

Applying Artificial Intelligence to Predict the Composition of Syngas Using Rice Husks: A Comparison of Artificial Neural Networks and Gradient Boosting Regression

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