
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Optimization and performance analysis of process parameters during anaerobic digestion of food waste using hybrid GRA-PCA technique

doi: 10.1063/1.4972884
Optimization and performance analysis of process parameters during anaerobic digestion of food waste using hybrid GRA-PCA technique
In this study, biogas production through anaerobic digestion of food waste was investigated by applying four factor-four level Taguchi design under experimental conditions such as solid concentration (5%–12.5% TS), pH (6–9), temperature (30–60 °C), and co-digestion of poultry waste (10%–40%). Multi-objective techniques such as grey relational analysis (GRA) and multi-variate principal component analysis (PCA) were used to determine the optimal level of process parameters. The interactive effect of process conditions on the biogas yield was studied with multi-response performance index. The obtained results were analyzed by analysis of variance and the percentage contributions of each parameter were determined. Optimum conditions for maximizing the biogas yield and volatile solid removal efficiency were determined using hybrid GRA-PCA technique and it was found to be solid concentration of 7.5% TS, pH of 7, temperature of 50 °C, and co-digestion of 30%. Supremacy of the chosen hybrid technique is confirmed from the confirmation experimental output.
3 Research products, page 1 of 1
- 2021IsAmongTopNSimilarDocuments
- 2021IsAmongTopNSimilarDocuments
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).33 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
