RSM-optimised slow pyrolysis of rice husk for bio-oil production and its upgradation

Das, Sutapa; Goud, Vaibhav V.

doi:10.1016/j.energy.2021.120161

Cited by 54 publications

(20 citation statements)

References 31 publications

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“…Response surface methodology (RSM) was used to construct experimental models and evaluate the effects of given factors on measured responses to obtain optimum results. Central composite design (CCD), which is considered a useful and efficient RSM design, proposes a minimum number of test runs and effectively determines experimental parameters, and is employed to develop the corresponding mathematical response surface equations 17–26 …”

Section: Introductionmentioning

confidence: 99%

“…Central composite design (CCD), which is considered a useful and efficient RSM design, proposes a minimum number of test runs and effectively determines experimental parameters, and is employed to develop the corresponding mathematical response surface equations. [17][18][19][20][21][22][23][24][25][26] The aim of this study was the optimization of a laboratory-scale pyrolysis process for pistachio seed and lignite valorization via a fast pyrolysis process toward biofuel production. In order to eliminate the disadvantages of the classical optimization method, CCD, one of the RSM design methods, has been used in this study.…”

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confidence: 99%

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Co‐pyrolysis of a coal/biomass blend into biofuel: optimization of operational parameters using central composite design

Оnаy

2022

Biofuels Bioprod Bioref

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Researchers are attempting to replace fossil and petro-based fuels with renewable and green fuels. Knowing the optimum values of pyrolysis parameters during the production of biofuel from biomass/ coal blends is important to obtain biofuel in the desired yield and quality. In this study, a central composite design was used in order to optimize pyrolysis parameters to obtain biofuel from the co-pyrolysis of a coal (lignite)/biomass (pistachio seeds) mixture in a well-swept resistance fixed bed reactor. Knowing the optimum values of different parameters affecting the biofuel yield and quality is very important in terms of the most efficient conditions and the economical production of energy. The effects of some operational parameters, like final temperature (factor A), heating rate (factor B) and percentage of lignite (factor C), were optimized through the central composite design method, and their behaviors were analyzed using analysis of variance. While the linear and quadratic effects of the final temperature and heating rate on the biofuel yield were significant, only the linear effect of the percentage of lignite was found to be important; on the other hand, the effects of the binary interaction between the factors were found to be insignificant. A quadratic equation was proposed to predict the behavior of the process under various conditions with an R 2 of 98.19. The best condition was predicted at a final temperature of 595 °C, a heating rate of 458 °C/min and a percentage lignite of 16.7% with maximum biofuel yield of 61.23%.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Co‐pyrolysis of a coal/biomass blend into biofuel: optimization of operational parameters using central composite design

Оnаy

2022

Biofuels Bioprod Bioref

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“…Among the experimental models in design of experiment, RSM is outstanding in many fields such as the chemistry, food science, and biology science [32][33][34][35]. In recent years, RSM has gradually gained favor in the engineering field [36][37][38][39], including in the oil-gas field development [40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Optimization and Analysis of CO2 Huff-n-Puff Process in Shale Oil Reservoirs Using Response Surface Methodology (RSM)

Wang

Xie

et al. 2022

Geofluids

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The objective of this study is to determine the influence of operational parameters of CO2 Huff-n-Puff EOR process in the Eagle Ford shale oil reservoirs using response surface methodology (RSM). Single-factor analysis was first conducted for establishing the Box-Behnken model in RSM. We selected the primary depletion time, gas injection time, cycle number, production time per cycle, and injection rate as the primary input variables using RSM. The cumulative oil production and net present value are optimized as the output factors. After that, Design of Expert 12 software was used to design the experimental table for the above setting factors. Corresponding to the results taken from the optimization, the most significant factor is injection rate, followed by injection time, cycle number, and primary depletion time, and production time per cycle is the least significant. Additionally, the optimum responses were found as primary depletion time of 2.37 years, injection time of 3.4 months, cycle number of 3, production time per cycle of 2.2 years, and injection rate of 5000 MSCF/D. Moreover, correlation coefficient (R2) of the regression model is 0.9977, and adjusted model R2 is 0.8898, which further indicates that the model has good reliability. Results show that RSM is a useful technique for optimization, and it also provides insights into optimizing and designing the CO2 Huff-n-Puff process in the shale oil reservoirs.

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“…It was found that the optimal bio-oil yield (36.5%) can be achieved at a temperature of 600 °C, a heating rate of 50 °C/min and a nitrogen flow rate of 11 L/min. Das and Gound (2021) used the RSM to optimize the process parameters of slow pyrolysis of rice husk. In order to determine the trend and relationship between the experimental responses and the process variables (temperature: 300-600 °C, nitrogen flow rate: 0.87-1.5 L/min, holding time: 20-60 min), a quadratic model was developed.…”

Section: Introductionmentioning

confidence: 99%

Response surface modelling of biomass-rich municipal solid waste pyrolysis: towards optimum hydrogen production

Tomasek

Egedy

Bocsi

et al. 2022

Clean Techn Environ Policy

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In this study, two-step pyrolysis of biomass-rich municipal solid waste was studied on nickel supported ZSM-5 catalyst. In the first stage of the reactor, constant temperature (T = 550 °C) was applied, and in the second stage, the reactions took place at 500, 700 and 850 °C. Effects of operating parameters (temperature = 500, 700, 850 °C, steam rate = 1, 5 g/h) and catalyst load (0.5, 1.0, 2.0) were studied on yields and compositions, particularly on the hydrogen contents. In order to determine the significance of the operating parameters, response surface methodology was used. Considering the experimental data, the values of hydrogen/carbon monoxide molar ratio, lower heating value and the simulation, it was found that the favourable operating parameters of two-step pyrolysis of biomass-rich municipal solid waste were 850 °C temperature and 1 g/h steam rate (gas yield: 27.1%, hydrogen yield: 9.96 mmol g−1 waste, hydrogen/carbon monoxide molar ratio: 1.8). From the data of response surface methodology, it was also concluded that temperature has a more critical effect on gas yields and composition than steam rate. However, in some cases, the synergistic effect of the two factors can also be significant. Graphical abstract

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RSM-optimised slow pyrolysis of rice husk for bio-oil production and its upgradation

Cited by 54 publications

References 31 publications

Co‐pyrolysis of a coal/biomass blend into biofuel: optimization of operational parameters using central composite design

Co‐pyrolysis of a coal/biomass blend into biofuel: optimization of operational parameters using central composite design

Optimization and Analysis of CO2 Huff-n-Puff Process in Shale Oil Reservoirs Using Response Surface Methodology (RSM)

Response surface modelling of biomass-rich municipal solid waste pyrolysis: towards optimum hydrogen production

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