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An integrated AHP-TOPSIS approach for bamboo product evaluation and selection in rural communities
(2024-09-01)
Chanpuypetch, Wirachchaya
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Niemsakul, Jirawan
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Atthirawong, Walailak
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Supeekit, Tuangyot
This study introduces a decision support model integrating the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select an economic tree product champion (bamboo) to benefit rural communities. An extensive literature review and expert discussions identified sixteen sub-criteria distributed across five main criteria. The study proposes four categories of bamboo products as alternatives, emphasizing community-level production capacity. The AHP determines priority weights, while TOPSIS prioritizes alternatives conducive to becoming the product champion within a community case study. The findings affirm the efficacy of Multi-Criteria Decision-Making (MCDM) in identifying a champion, with “Value addition potential,” “Domestic market demand,” and “International market (export) demand” identified as pivotal criteria. Bamboo culm-based products for energy-related applications emerged as the chosen product champion in a community case study in Thailand. This study offers practical implications for rural communities and potential investors in economic tree ventures, allowing the customization of decision criteria and alternatives for specific contexts. Socially, the focus on bamboo highlights diverse benefits along the entire supply chain, from upstream to downstream. The research pioneers a decision support model, providing insights into market opportunity analysis and supply chain network design based on the selected product champion.
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On-line measurement of activation energy of ground bamboo using near infrared spectroscopy
(2019-04-01)
Sirisomboon, Panmanas
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Posom, Jetsada
On-line measurement of activation energy (Ea) is very important in supporting the thermal conversion process. The main objective of this study was to evaluate the Ea of ground bamboo using near infrared spectroscopy in real time. 80 bamboo samples with different diameters were selected using random sampling. Ea was determined using the Coats-Redfern method, and Ea of reaction order (n) at n = 1 and n≠1 was investigated. The performance of on-line measurement predicted by PLS modelling for Ea at n = 1 and Ea at n≠1 showed coefficients of determination of 0.781 and 0.714, respectively; standard error of prediction of 5.249 and 6.858 kJ/mol, respectively; and bias values of −1.0628 and −1.871 kJ/mol, respectively. Both PLS models were found to be fair and could be applied toward screening. The results showed that the vibration bands of lignocellulosic components (CH<inf>2</inf>, hemicellulose, cellulose, and lignin) highly influenced model development. Moreover, internal relationships were identified among Ea, the pre-exponential factor (A), and n, such as A (1/min) = 63251 × e0.2200×Ea (at n = 1), A (1/min) = 33719 × e0.2267×Ea (at n≠1), and n = 0.008 × Ea+0.254. These relationships can be used to evaluate A and n if Ea is known. In the case of this study, Ea was forecasted using an NIR model.
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Preparation of activated carbon from bamboo-cellulose fiber and its use for EDLC electrode material
(2017-04-01)
Fujishige, Masatsugu
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Yoshida, Ichiro
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Toya, Yumiko
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Banba, Yasuo
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Oshida, Kyo ichi
Carbonization and post activation of bamboo-cellulose fiber was carried out. The carbonization was performed at 600°C, 800°C and 1000°C in argon atmosphere. Then, they were activated by heating solid mixture of carbonized bamboo and sodium hydroxide (NaOH) at 720°C in argon atmosphere. The largest specific surface area of the resulting activated carbon (carbonized at 600°C) was 2366m2/g with the micropore volume of 0.71cm3/g and mesopore volume of 0.06cm3/g. It was found that the carbonization temperature is very important to obtain nanoporous carbon with large specific surface area. The distributions of interlayer spacing were estimated from the power spectra of the TEM images of the carbonized samples. It showed the interlayer spacing of basic structural unit (BSU) decreased from 0.49nm (BC-0600) through 0.47nm (BC-0800) to 0.45nm (BC-1000). The activated carbon was used as the host material of the electrodes of coin type electric double-layer capacitor (EDLC) with organic electrolyte. The observed specific capacitance was 43F/g (23F/cm3) for the activated carbon (carbonized at 600°C), comparable to 44F/g (22F/cm3) of commercial activated carbon (MSP). The corresponding values for the activated carbons (carbonized at 800°C and 1000°C) were 40F/g (23F/cm3) and 17F/g (12F/cm3), respectively.
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Evaluation of pyrolysis characteristics of milled bamboo using near-infrared spectroscopy
(2017-01-01)
Posom, Jetsada
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Saechua, Wanphut
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Sirisomboon, Panmanas
This paper reports the development of a rapid and low-cost method based on near-infrared spectroscopy as an alternative for thermogravimetric determination of the pyrolysis characteristics, including T<inf>onset</inf>, T<inf>sh</inf>, T<inf>peak</inf>, T<inf>offset</inf>and DTG<inf>peak</inf>, of milled bamboo. T<inf>onset</inf>is the extrapolated onset temperature that is calculated from the partial peak resulting from the decomposition of the hemicellulose component, T<inf>sh</inf>is the temperature corresponding to the overall maximum of the hemicellulose decomposition rate, DTG<inf>peak</inf>is the overall maximum of the cellulose decomposition rate, T<inf>peak</inf>is the temperature corresponding to the overall maximum of the cellulose decomposition rate and T<inf>offset</inf>is the extrapolated offset temperature of the DTG<inf>peak</inf>curves determined using thermogravimetric analysis (TGA). The models may be used to control the pyrolysis processes of bamboo to achieve the most economical and environmental conditions. 80 samples of bamboo with various circumferences of culms in the ranges of approximately 16–18, 18–20, 20–22, 22–24, 24–26, 26–28, 28–30, 30–32, 32–34, 34–36, 36–38 and 38–40 cm were randomly collected for optimization of the models. The models were optimized by partial least squares regression (PLSR) with 80% of samples for the calibration set and 20% for the validation set. For T<inf>onset</inf>, T<inf>sh</inf>, T<inf>peak</inf>, T<inf>offset</inf>and DTG<inf>peak</inf>the models showed coefficients of determination (R2) of 0.566, 0.845, 0.917, 0.973, and 0.671; root mean square errors of prediction (RMSEP) of 9.7 °C, 4.36 °C, 3.77 °C, 2.66 °C, and 0.428 wt loss %/min; ratios of prediction to deviation (RPD) of 1.52, 2.58, 3.48, 3.55, and 1.75; and biases of −0.344 °C, −0.765 °C, 0.349 °C, −5.41 °C, and 0.045 wt loss %/min, respectively. In addition, the results showed that pyrolysis characteristics did not depend on the circumference. The vibrational bands of water and CH<inf>3</inf>, O[sbnd]H stretch, first overtones of Ar–OH, CH<inf>2</inf>and HC[dbnd]CH in the cellulose and lignin structures, O[sbnd]H hydrogen bonds of polyvinyl alcohol and C[sbnd]H stretch corresponding to the first overtone of CH<inf>2</inf>had the highest influence on the values of T<inf>onset</inf>, T<inf>sh</inf>, T<inf>peak</inf>, and T<inf>offset</inf>, respectively. The vibrational band of the C[sbnd]O[sbnd]C asymmetrical stretches of cellulose and hemicellulose, and the combination of O[sbnd]H stretch and HOH bend of polysaccharides influenced the DTG<inf>peak</inf>value. These results are beneficial for studying the thermal behaviour of milled bamboo as a potential resource for producing biofuels, especially in the pyrolysis process.
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Evaluation of lower heating value and elemental composition of bamboo using near infrared spectroscopy
(2017-01-01)
Posom, Jetsada
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Sirisomboon, Panmanas
This study was to optimize models using near infrared spectroscopy for evaluation of lower heating value, carbon, hydrogen, nitrogen, sulfur and oxygen content of bamboo. Partial least squares regression was performed using 80 samples of bamboo where 64 samples was randomly assigned for calibration and 16 samples for validation. The result was that lower heating value and element composition did not depend on circumference size. The models showed the coefficient of determination of validation set and ratio of standard error of prediction to standard deviation of reference value of 0.934 and 3.96 for lower heating value, 0.803 and 2.31 for carbon; 0.856 and 2.65 for hydrogen; 0.973 and 6.6 for nitrogen; 0.785 and 2.19 for sulfur and 0.522 and 1.46 for oxygen, respectively. Models for lower heating value, nitrogen and hydrogen content prediction provided the highest performance, which could be used for most application. The carbon and sulfur models were fair and oxygen model was poor. The result could be a guide for applying in bamboo trading as biomass, in design and operation control of energy conversion and in predicting flue gas flow rate, air requirement, and flue gas compositions in combustion, gasification or pyrolysis.

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