Simulation of Arc Plasma Gasification Based on Experimental Conditions

An EPJ process simulation model was set up and verified to simulate the plasma gasification process of the medical wastes. The influence of ER value and SAMR value was simulated based on experimental conditions including material feeding rate, furnace temperature and medical waste properties. Result...

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Main Authors: Cao Yawen, Li Bin, Wang Qin, Zhang Zhihao, Han Xianwei
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/54/e3sconf_icaeer2020_05029.pdf
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spelling doaj-e68ab6e109f94da7b174c5451eabf2482021-04-02T13:07:39ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011940502910.1051/e3sconf/202019405029e3sconf_icaeer2020_05029Simulation of Arc Plasma Gasification Based on Experimental ConditionsCao Yawen0Li Bin1Wang Qin2Zhang Zhihao3Han Xianwei4Shaanxi Key Laboratory of Plasma Physics and Applied TechnologyAcademy of Aerospace Propulsion TechnologyState Key Laboratory of Clean Energy Utilization, Zhejiang UniversityShaanxi Key Laboratory of Plasma Physics and Applied TechnologyShaanxi Key Laboratory of Plasma Physics and Applied TechnologyAn EPJ process simulation model was set up and verified to simulate the plasma gasification process of the medical wastes. The influence of ER value and SAMR value was simulated based on experimental conditions including material feeding rate, furnace temperature and medical waste properties. Results shows that ER=0.3 is a turning point for medical waste plasma gasification. The required input plasma power and volume flow of combustible constituents in syngas reach the maximum at ER=0.3. The balance of syngas composition and required input plasma power should be overall considered. Results shows that the SAMR value mainly influences the amount of H element and N element in the system at a fixed ER value, thus influencing the proportions of H2 and N2 in monotonous ways. Input plasma power needed and combustible syngas flow increase with the increasing SAMR.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/54/e3sconf_icaeer2020_05029.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Cao Yawen
Li Bin
Wang Qin
Zhang Zhihao
Han Xianwei
spellingShingle Cao Yawen
Li Bin
Wang Qin
Zhang Zhihao
Han Xianwei
Simulation of Arc Plasma Gasification Based on Experimental Conditions
E3S Web of Conferences
author_facet Cao Yawen
Li Bin
Wang Qin
Zhang Zhihao
Han Xianwei
author_sort Cao Yawen
title Simulation of Arc Plasma Gasification Based on Experimental Conditions
title_short Simulation of Arc Plasma Gasification Based on Experimental Conditions
title_full Simulation of Arc Plasma Gasification Based on Experimental Conditions
title_fullStr Simulation of Arc Plasma Gasification Based on Experimental Conditions
title_full_unstemmed Simulation of Arc Plasma Gasification Based on Experimental Conditions
title_sort simulation of arc plasma gasification based on experimental conditions
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description An EPJ process simulation model was set up and verified to simulate the plasma gasification process of the medical wastes. The influence of ER value and SAMR value was simulated based on experimental conditions including material feeding rate, furnace temperature and medical waste properties. Results shows that ER=0.3 is a turning point for medical waste plasma gasification. The required input plasma power and volume flow of combustible constituents in syngas reach the maximum at ER=0.3. The balance of syngas composition and required input plasma power should be overall considered. Results shows that the SAMR value mainly influences the amount of H element and N element in the system at a fixed ER value, thus influencing the proportions of H2 and N2 in monotonous ways. Input plasma power needed and combustible syngas flow increase with the increasing SAMR.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/54/e3sconf_icaeer2020_05029.pdf
work_keys_str_mv AT caoyawen simulationofarcplasmagasificationbasedonexperimentalconditions
AT libin simulationofarcplasmagasificationbasedonexperimentalconditions
AT wangqin simulationofarcplasmagasificationbasedonexperimentalconditions
AT zhangzhihao simulationofarcplasmagasificationbasedonexperimentalconditions
AT hanxianwei simulationofarcplasmagasificationbasedonexperimentalconditions
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