DYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC)

Microbial Fuel Cell (MFC) as alternative renewable energy has piqued researchers’ interest, but the low power density of MFC requires further development. Various factors affect the performance of MFC, but performing all variations will be costly and time-consuming. As a solution, mathematical model...

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Main Author: Gilbert
Format: Final Project
Language:Indonesia
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Online Access:https://digilib.itb.ac.id/gdl/view/78556
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Institution: Institut Teknologi Bandung
Language: Indonesia
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spelling id-itb.:785562023-10-23T14:40:53ZDYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC) Gilbert Teknik (Rekayasa, enjinering dan kegiatan berkaitan) Indonesia Final Project biofilm, cell potential, electrode, mathematical modeling, power density INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/78556 Microbial Fuel Cell (MFC) as alternative renewable energy has piqued researchers’ interest, but the low power density of MFC requires further development. Various factors affect the performance of MFC, but performing all variations will be costly and time-consuming. As a solution, mathematical models of MFC are developed to simulate the effect of the abovementioned factors. The previous mathematical model developed in Institut Teknologi Bandung only covers the steady-state of MFC, and no dynamic model has been developed. This research is comprised of four stages, namely literature study, modification, validation, and simulation. The developed model will cover both dynamic and steady-state models. The base model for the development of dynamic model is Esfandyari (2017), meanwhile for the steady-state model are Zeng (2010) and Oliveira (2018) with further modification by Kautsar & Sualing (2021). Dynamic modeling will determine the effect of microbe types on the formation of biofilm and steady-state OCV. The OCV obtained will then be used in the steady-state model to determine the maximum power density and its’ corresponding voltage. The results for the dynamic model show similarity with the results conducted by Suryaga (2017). The highest value of steady-state OCV was observed in heterotrophic biomass at 838.93 mV in 75-100 hours (±3-4 days) with a biofilm thickness of 2.098 x 10-4 m, meanwhile, the lowest value was observed in C. sporogenes at 837.77 mV in 450-475 hours (±18-19 days) with a biofilm thickness of 2.089 x 10-4 m. In the steady-state simulation, at current density 87.83 mA/m2, resulting highest power density and voltage was observed in heterotrophic biomass 2050.12 mW/m2 and 408.16 mV, meanwhile the lowest was observed in anaerobic microbial communities at 8.48 mW/m2 and 90.43 mV. A general trend was observed where microbial variations with higher ?max and lower Ks results in higher steady-state OCV in the shortest amount of time while increasing power density and its’ corresponding voltage. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
topic Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
spellingShingle Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
Gilbert
DYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC)
description Microbial Fuel Cell (MFC) as alternative renewable energy has piqued researchers’ interest, but the low power density of MFC requires further development. Various factors affect the performance of MFC, but performing all variations will be costly and time-consuming. As a solution, mathematical models of MFC are developed to simulate the effect of the abovementioned factors. The previous mathematical model developed in Institut Teknologi Bandung only covers the steady-state of MFC, and no dynamic model has been developed. This research is comprised of four stages, namely literature study, modification, validation, and simulation. The developed model will cover both dynamic and steady-state models. The base model for the development of dynamic model is Esfandyari (2017), meanwhile for the steady-state model are Zeng (2010) and Oliveira (2018) with further modification by Kautsar & Sualing (2021). Dynamic modeling will determine the effect of microbe types on the formation of biofilm and steady-state OCV. The OCV obtained will then be used in the steady-state model to determine the maximum power density and its’ corresponding voltage. The results for the dynamic model show similarity with the results conducted by Suryaga (2017). The highest value of steady-state OCV was observed in heterotrophic biomass at 838.93 mV in 75-100 hours (±3-4 days) with a biofilm thickness of 2.098 x 10-4 m, meanwhile, the lowest value was observed in C. sporogenes at 837.77 mV in 450-475 hours (±18-19 days) with a biofilm thickness of 2.089 x 10-4 m. In the steady-state simulation, at current density 87.83 mA/m2, resulting highest power density and voltage was observed in heterotrophic biomass 2050.12 mW/m2 and 408.16 mV, meanwhile the lowest was observed in anaerobic microbial communities at 8.48 mW/m2 and 90.43 mV. A general trend was observed where microbial variations with higher ?max and lower Ks results in higher steady-state OCV in the shortest amount of time while increasing power density and its’ corresponding voltage.
format Final Project
author Gilbert
author_facet Gilbert
author_sort Gilbert
title DYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC)
title_short DYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC)
title_full DYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC)
title_fullStr DYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC)
title_full_unstemmed DYNAMIC AND STEADY MODEL DEVELOPMENT OF TWO-CHAMBER BATCH MICROBIAL FUEL CELL (MFC)
title_sort dynamic and steady model development of two-chamber batch microbial fuel cell (mfc)
url https://digilib.itb.ac.id/gdl/view/78556
_version_ 1822008608754237440