KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Author: search.filters.author.Pambudi, SuluhSubject: search.filters.subject.Spent coffee grounds

Search Results

Now showing 1 - 3 of 3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Explainable machine learning for predicting thermogravimetric analysis of oxidatively torrefied spent coffee grounds combustion
    (2025-04-01)
    Pambudi, Suluh
    ;
    Jongyingcharoen, Jiraporn Sripinyowanich
    ;
    Saechua, Wanphut
    Understanding the combustion behavior of oxidatively torrefied spent coffee grounds (SCG) is crucial for advancing sustainable fuel technologies. This study introduces a novel, explainable machine learning (ML) framework as a cost-effective alternative to traditional thermogravimetric analysis (TGA) that is designed to accelerate the evaluation of oxidatively torrefied SCG combustion properties. Four ML models: artificial neural network (ANN), k-nearest neighbor (k-NN), random forest (RF), and decision tree (DT), were compared to predict TGA data using proximate analysis and combustion temperature (CT). Among the evaluated models, k-NN exhibited the highest performance, achieving near-perfect R<sup>2</sup> values that exceeded 0.9904 and RMSE values below 0.9552 on the validation set for both TG (mass loss) and DTG (derivative mass loss). It also accurately predicted key combustion properties, including ignition, peak, and burnout temperature when tested on unknown data. LIME (Local Interpretable Model-agnostic Explanations) analysis revealed that CT was the most influential predictor for TG and DTG, enhancing model interpretability. The results highlight the effectiveness of the k-NN-LIME approach in analyzing the combustion of oxidatively torrefied SCG, offering a robust and explainable model with significant implications for bioenergy research and sustainable fuel development.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Thermochemical treatment of spent coffee grounds via torrefaction: A statistical evidence of biochar properties similarity between inert and oxidative conditions
    (2024-03-01)
    Pambudi, Suluh
    ;
    Jongyingcharoen, Jiraporn Sripinyowanich
    ;
    Saechua, Wanphut
    This study used several statistical analyses to explore the impact of both inert and oxidative conditions on the characteristics of biochar derived from the torrefaction of spent coffee grounds (SCG). The study also considered variations in torrefaction temperature and residence time. Various fuel analyses were conducted, including high heating value (HHV), torrefaction index, proximate characteristics, thermogravimetric analysis (TGA), hygroscopicity, and Fourier-transform infrared spectroscopy (FTIR). The analysis of variance (ANOVA) revealed that the influence of both inert and oxidative conditions on HHV and mass yield was insignificant (p ≥ 0.05). Moreover, considering the same temperature and residence time, principal component analysis (PCA) and hierarchical cluster analysis (HCA) identified oxidative and inert conditions belonging to the same group or cluster. This finding indicated that neither atmospheric condition significantly affected the characteristics of the biochar measured in this research. Therefore, oxidative torrefaction offers significant advantages as it can produce biochar of comparable quality under inert conditions.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    A thermogravimetric assessment of eco-friendly biochar from oxidative torrefaction of spent coffee grounds: Combustion behavior, kinetic parameters, and potential emissions
    (2024-02-01)
    Pambudi, Suluh
    ;
    Saechua, Wanphut
    ;
    Jongyingcharoen, Jiraporn Sripinyowanich
    This study investigated how temperature and residence time variations impact the combustion behavior, kinetic, and potential emissions of biochar produced through oxidative torrefaction of spent coffee grounds (SCG). The study examined the characteristics of combustion and kinetics by conducting thermogravimetry analysis under heating rates of 10 °C·min<sup>−1</sup>. The Coats-Redfern model was utilized to calculate kinetic parameters. While the emission indices were approximated using the data obtained from elemental analysis. The results indicated that biochar's comprehensive combustion index (C<inf>ci</inf>) from oxidative torrefaction was lower than that of raw SCG, suggesting stable combustion behavior. Moreover, with the escalation of torrefaction intensity, the activation energy (E<inf>a</inf>) values exhibited an upward trend for the char combustion stage, ranging from 22.08 kJ mol<sup>−1</sup> to 38.46 kJ mol<sup>−1</sup>. Concurrently, the E<inf>a</inf> values pertaining to the oxidative pyrolysis stage decreased from 64.26 kJ mol<sup>−1</sup> to 52.65 kJ mol<sup>−1</sup>. Besides, this study emphasized that the ash content of the biochar was lower than that of coal and remained consistent with the ash content of raw SCG (p > 0.05). Moreover, the study revealed that biochar from oxidative torrefaction emitted less CO<inf>2</inf> (67.35 g MJ<sup>−1</sup>) than lignite coal (76.55 g MJ<sup>−1</sup>). Additionally, biochar exhibited up to 27 times lower dust emissions than bituminous coal, emphasizing its eco-friendly fuel potential.