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Valorisation of hazardous medical waste using steam injected plasma gasifier: a parametric study on the modelling and multi-objective optimisation by integrating Aspen plus with RSM
Environmental Technology ( IF 2.2 ) Pub Date : 2021-09-09 , DOI: 10.1080/09593330.2021.1946599
Deepak Kumar Singh 1 , Jeewan V Tirkey 1
Affiliation  

ABSTRACT

The COVID-19 Pandemic has a detrimental effect on the environment related to the exponential rise in medical waste (MW). Extraction of energy from the toxic MW with the latest gasification technology instead of conventional incineration is of utmost importance to promote sustainable development. This present study investigates the processing of MW for the generation of enriched hydrogen syngas using steam injected plasma gasifier. Modelling of Plasma gasifier was performed in Aspen Plus and Model validation was done with the experimental result and, a good agreement was attained. Sensitivity analysis was implemented on MW in which the influence of gasification temperature, equivalence ratio (ER), and Steam/Biomass (S/B) on the producer gas (PG) composition, gas yield, H2/CO ratio, cold gas efficiency (CGE), and the higher heating value (HHV) was calculated. Furthermore, Response surface methodology (RSM) has been incorporated for the multi-objective optimisation of the variable gasification parameters. R2 values obtained from ANOVA for H2, CGE, and HHV are 98.62%, 99.10%, and 98.9% respectively. Using the response optimiser, the optimum values of H2, CGE, and HHV were found to be 0.43 (mole frac), 89.95%, and 7.49 MJ/Nm3 for temperature at 1560.60°C, equivalence ratio 0.1, and S/B 0.99, respectively. The observed coefficient of desirability was about 0.97.



中文翻译:

使用蒸汽喷射等离子气化器对危险医疗废物进行增值:通过集成 Aspen plus 与 RSM 进行建模和多目标优化的参数研究

摘要

COVID-19 大流行对与医疗废物 (MW) 呈指数增长相关的环境产生不利影响。用最新的气化技术而不是传统的焚烧从有毒的 MW 中提取能量对于促进可持续发展至关重要。本研究研究了使用蒸汽喷射等离子气化器处理 MW 以产生富氢合成气。在 Aspen Plus 中对等离子气化炉进行了建模,并与实验结果进行了模型验证,得到了很好的一致性。对 MW 进行敏感性分析,其中气化温度、当量比 (ER) 和蒸汽/生物质 (S/B) 对发生炉煤气 (PG) 组成、产气量、H 2的影响计算 /CO 比、冷气效率 (CGE) 和高热值 (HHV)。此外,响应面方法 (RSM) 已被纳入可变气化参数的多目标优化。从 ANOVA 获得的 H 2 、CGE 和 HHV 的R 2值分别为 98.62%、99.10% 和 98.9%。使用响应优化器,发现 H 2、CGE 和 HHV的最佳值为0.43(摩尔分数)、89.95% 和 7.49 MJ/Nm 3(温度为 1560.60°C、当量比为 0.1 和 S/B) 0.99,分别。观察到的合意系数约为 0.97。

更新日期:2021-09-09
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