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Enhanced stability of pulverized biomass flames using an expanded primary port with bluff body
(2026-01-01)
Laphirattanakul, Ponepen
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Siripoom, Pongsakorn
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Keawchompoo, Chatchalerm
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Charoensuk, Jarruwat
The impact of bluff body geometry combined with primary exit port expansion on the flame stability of a biomass pulverized fuel burner was investigated through numerical simulations. The expansions, applied at 1.25 and 1.5 times the original port size while maintaining a constant blockage ratio, were intended to reduce the momentum ratio between primary and secondary air streams. However, this adjustment concurrently led to a decrease in the swirl number, primarily due to the reduction in the secondary air exit area. Experimental results from the base case configuration were employed for model validation. Among the turbulence models considered, the SST k-ω model demonstrated the best agreement with experimental data in terms of temperature distribution and emission characteristics. The simulation results revealed that the base case exhibited flame anchoring behind the bluff body, supported by a pronounced reverse velocity region in its wake. Flame stability was also achieved in the 1.5SB case, attributed to a sufficiently reduced momentum ratio. This reduction enhanced the entrainment of the secondary air stream, promoting greater dispersion of fuel particles and enabling early-stage volatile combustion. The 1.5SB configuration achieved the highest temperature among all cases, reaching approximately 1150 °C. In contrast, the 1.25SB case exhibited flame blowout, resulting from a combination of reduced swirl number and an insufficient reduction in momentum ratio.
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Identification and Removal of Negative Biomass Samples via Scatter Plot Analysis to Improve GWP Predictive Modeling
(2025-11-13)
Gyawali, Prakash
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Shrestha, Bijendra
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Posom, Jetsada
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Pornchaloempong, Pimpen
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Sirisomboon, Panmanas
Accurate prediction of Global Warming Potential (GWP) from biomass constituents is essential for evaluating the sustainability of bioenergy sources. However, the inclusion of biomass samples with weak or negative correlation to key elemental components such as Carbon (C). Hydrogen (H). Nitrogen (N). and Oxygen (O)'can reduce model accuracy and lead to misleading conclusions. This study utilizes scatter plot regression analysis to evaluate and remove "negative biomass samples."defined as those with consistently low R2 values across constituent-GWP relationships using HHV = 0.2949C + 0.82 50H developed for wood biomass by Yin. Regression models were generated for each biomass species using elemental concentrations as predictors of GWP. Notably, several non-wood species (e.g.. Zea Mays-Shell. Bagasse. Bamboo) exhibited very low R- values (often <0.05) for model between elemental composition and GWP. where all elemental correlations indicated weak predictive relationships. In contrast, wood-based species such as Alnus demonstrated significantly higher R2 values, especially with Carbon (R2 = 0.69). Hydrogen (R2 = 0.57). and Oxygen (R2 = 0.68), suggesting a stronger linear influence on GWP. Removing these low-contributing samples improved the clarity and reliability of the predictive model related to HHV and each type of element (C.H.N and O) as evidenced by a sharper regression slope of a graph plotted between predicted GWP and measured GWP of positive species and better fit (increased R2) for the remaining samples. These results highlight the value of preliminary scatter plot analysis in identifying biomass species that obscure rather than support predictive modeling. This filtering step ultimately enhances the robustness and inteipretability of constituent-based GWP prediction frameworks, particularly when applying FT-XIR spectroscopy and chemometric modelling.
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Carbon capture through solar-driven CO2 gasification of oil palm empty fruit bunch to produce syngas and biochar
(2025-05-15)
Al-Muraisy, Saqr A.A.
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Chuayboon, Srirat
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Soares, Lais Americo
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Buijnsters, J. G.
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Ismail, Shahrul bin
Oil palm empty fruit bunch (OPEFB) is an abundant organic waste in Malaysia that is often disposed of through field burning. A previous study has shown that solar-driven steam gasification of OPEFB can produce hydrogen-rich syngas with an energy upgrade factor of 1.2 and a carbon conversion efficiency of 95.1 %. Beyond its potential as a biofuel, OPEFB can also act as a carbon sink, capturing photosynthetically stored carbon. This study explores the potential of amplifying OPEFB's negative carbon emissions through solar-driven gasification, using CO<inf>2</inf> as the gasifying agent. In this work, a Central Composite Design (CCD) approach was employed to assess the influence of temperature (1100–1300 °C) and CO<inf>2</inf>/OPEFB molar ratio (1.6–3.0) on H<inf>2</inf>/CO molar ratio and energy upgrade factor, with a constant OPEFB flow rate of 1.8 g/min. The results demonstrated that at an energy upgrade factor of 1.4, 94.9 % of the total carbon was converted into syngas with a H<inf>2</inf>/CO molar ratio of 0.3. The maximum observed net carbon capture yield of 0.4 g C/g OPEFB was achieved at 1300 °C and a CO<inf>2</inf>/OPEFB molar ratio of 3.0. The remaining carbon (94.4–95.7 wt %) was converted into biochar with low heavy metal content, which has potential as a soil enhancer.
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Sustainable Production of Biomethanol and Its Environmental Impacts
(2025-01-01)
Detchusananard, Thanaphorn
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Im-Orb, Karittha
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Wiranarongkorn, Kunlanan
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Chen, Yong Song
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Arpornwichanop, Amornchai
Utilizing biomass and biogas sourced from various organic waste materials as renewable feedstocks for biomethanol production offers a sustainable alternative to fossil fuels such as coal, petroleum oil, and natural gas. This chapter provides an exploration of several technologies employed in biomethanol production, including biomass gasification, biomass pyrolysis, and biogas upgrading. Syngas production and conditioning, methanol synthesis and separation, and integrating systems with other renewable energy sources are found to be crucial stages towards achieving sustainable production. The chapter comprehensively evaluates the technical, economic, and environmental aspects of each biomethanol production process. Furthermore, it delves into ongoing efforts to improve and develop biomethanol-production processes to achieve the carbon neutrality goals. The chapter also outlines emerging trends and future research directions in the field of biomethanol production.
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Performance Analysis of Biomass Gasification with Biogas Co-Feeding for Hydrogen Production
(2025-01-01)
Saebea, Dang
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Patcharavorachot, Yaneeporn
To improve the hydrogen yield in biomass gasification, the addition of biogas for co-feeding with biomass in gasification was proposed in this work. The gasification model developed in Aspen Plus software was validated with experimental data. The performance of biomass gasification with biogas co-feeding using steam as a gasifying agent was investigated. The effect of the steam-to-fuel ratio on the gasification of mixed biomass and biogas was studied. The results show that the simulation results of biomass gasification were consistent with experimental data. Biomass gasification with biogas co-feeding can raise the amount of hydrogen and carbon monoxide in gas products by 22.12% and 18.44%, respectively. Moreover, the increase in the steam-to-fuel ratio enhances hydrogen in syngas. However, the system efficiency decreases with increasing steam-to-fuel ratio.
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Techno-economic performance analysis of biomass-to-methanol with solid oxide electrolyzer for sustainable bio-methanol production
(2024-12-30)
Detchusananard, Thanaphorn
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Wiranarongkorn, Kunlanan
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Im-orb, Karittha
The analysis of the technical and economic performance of an integrated biomass to methanol and solid oxide electrolysis process (BtM-SOEC) is studied to find more sustainable process of bio-methanol production. The oil palm empty fruit branch (EFB) which is abundant in Thailand is used as biomass feedstock. Modeling of the BtM-SOEC is done using Aspen Plus. For technical aspects, the production rate of oxygen and hydrogen from the SOEC can be enhanced through an appropriate adjustment of the number of cells and cell temperature. The BtM-SOEC offers higher methanol yield and overall efficiency, while consumes less energy than the conventional biomass to methanol process (BtM). The maximum methanol production rate of 0.4995 kmol hr−1 derived from BtM-SOEC is achieved at a number of cells of 325 cells and a cell temperature of 700 °C, at this condition the overall efficiency is 64.79 %. The economic assessment indicates that the conventional BtM and BtM-SOEC are still not economically feasible. However, the conventional BtM is more economically feasible than the BtM-SOEC. The methanol cost of BtM-SOEC can turn out to be economically feasible when renewable electricity cost and SOEC cost decrease substantially. The methanol cost of the BtM-SOEC (620 USD ton−1) can be competitive to that of the BtM (703 USD ton−1) when the cost of input renewable electricity decreases by 80 %. Consequently, this research highlights the potential of BtM-SOEC from agricultural residues for sustainable bio-methanol production in the future market condition that the cost of renewable electricity tends to continuously decrease with the technology development and increased technology adoption and the carbon policy tends to be tightened to relieve global warming.
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Co-pyrolysis of biomass/polyurethane foam waste: Thermodynamic study using Aspen Plus
(2024-10-01)
Patcharavorachot, Yaneeporn
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Pradiskhean, Supanat
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Aentung, Tanawat
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Saebea, Dang
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Arpornwichanop, Amornchai
Due to the varieties and identical feature of solid waste, this research aims to consider the use of various feedstocks in pyrolysis process for liquid fuel production. The feedstock considered covers woody and non-woody biomass and plastic waste which are represented by sawdust (SD), palm leaf (PL) and polyurethane foam (PU) waste. In this research, both pure solid waste and the co-pyrolysis of biomass and plastic wastes were determined based on thermodynamics study. The model of pyrolysis process developed through Aspen Plus simulator was implemented to study the product yield, higher heating value (HHV) and energy consumption with a wider range of pyrolysis temperature and blending weight ratio. The simulation results clearly showed that the use of pure PU waste can provide the highest oil yield (∼44 wt%) which is corresponded to highest HHV (∼28 MJ/kg). The pyrolysis, operating at 400 °C, can provide the most significant quantity of oil. For the co-pyrolysis, the results revealed that more PU waste blended in both biomasses can improve both oil yield and HHV while the energy consumption is lower. From the simulation results, the optimal blending weight ratio of biomass and PU waste at 25:75 can provide suitable oil yield (∼43 wt%), HHV (∼26 MJ/kg) and energy consumption (243 kW).
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Development of seasoning powder from foam-mat dried Artemia franciscana biomass
(2024-09-01)
Thuy, Nguyen Minh
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Anh, Nguyen Ngoc Huong
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Xuyen, Nguyen Thi Kim
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Vi, Nguyen Hoang Yen
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Quyen, Nguyen Hoang Thuy
Seasoning powder was commonly produced from meat or poultry. In this research, it was produced from foam mat– dried Artemia powder with the addition of various spices. Six mixing formulas were created with Artemia powder ratios ranging from 60% to 35% (from A1 to A6) along with other spice ingredients such as sugar, salt, pepper powder, shallots powder, and monosodium glutamate (MSG) and analyzed for quality and sensory characteristics. The results showed that the highest protein content was achieved in sample A1 (48.3%) and the lowest in sample A6 (28.2%). Sample A5 (ratio of Artemia powder/sugar/salt/pepper powder/onion powder/MSG is 40:26:24:2:3:5) achieved the highest sensory score, followed by sample A4 (ratio of Artemia powder/sugar/salt/pepper/onion powder/ MSG is 45:23:22:2:3:5). The remaining samples (A1, A2, A3, and A6) had lower sensory scores. Microstructural image analysis (from scanning electron microscope) of sample A5 showed good uniformity, high nutritional value, especially high protein content (about 3.06–3.48 times) compared to other existing seasoning powder products on the market, and very good water-binding capacity.
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Evaluation of pyrolysis characteristics and kinetic parameters from several prospected biomass residues by thermogravimetric analysis
(2024-01-01)
Pambudi, S.
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Jongyingcharoen, J. S.
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Saechua, W.
With fossil fuel supplies dwindling and persistent environmental concerns surrounding their consumption, biomass has emerged as a highly promising renewable energy source. Understanding the characteristics of biomass pyrolysis is crucial as it provides valuable insights and guidance for designing and optimizing the pyrolysis process. In this regard, a thermogravimetric assessment was conducted to evaluate the pyrolysis characteristics and kinetic parameters of four prospective biomass sources: Yang Na wood (Dipterocarpus alatus), palmyra palm shell, cotton stalk, and spent coffee grounds with a condition temperature range of 33 °C to 700 °C and a heating rate of 10 °C·min-1 in a nitrogen atmosphere. The kinetic parameters were evaluated using the Coats and Redfern methods, employing various reaction order models. The activation energy and pre-exponential factor were determined for the active pyrolysis stage. The results revealed that the high heating values for all samples ranged from 18.20 to 23.00 MJ·kg-1. Additionally, the onset temperature fell within the range of 243 to 254 °C, while the offset temperature ranged from 365 to 452 °C for all samples. The conversion rate at the offset temperature was 0.67 for Yang Na wood, 0.62 for palmyra palm shell, 0.65 for cotton stalk, and 0.74 for spent coffee grounds. Moreover, the activation energies were measured as 46.47 kJ·mol-1 for Yang Na wood, 52.46 kJ·mol-1 for palmyra palm shell, 64.20 kJ·mol-1 for cotton stalk, and 69.01 kJ·mol-1 for spent coffee grounds. The higher activation energy corresponded to a higher pre-exponential factor. In conclusion, the pyrolysis characteristics and kinetic parameters of the four types of biomasses have been found to be favourable, indicating their potential for promotion and application as a raw material for the pyrolysis process.
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Evaluating limit of detection and quantification for higher heating value and ultimate analysis of fast-growing trees and agricultural residues biomass using NIRS
(2023-10-09)
Shrestha, Bijendra
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Shrestha, Zenisha
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Posom, Jetsada
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Sirisomboon, Panmanas
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Shrestha, Bim Prasad
Accurate non-destructive assessment of biomass energy properties is essential for optimizing its use as an alternative fuel. In this study, 200 biomass samples were used to determine higher heating value (HHV) and 120 biomass samples for analyzing ultimate analysis parameters using near-infrared spectroscopy within the full wavenumber range of 12489.48 – 3594.87 cm-1. The samples were grounded, and five different types of partial least squares regression (PLSR) models were developed using traditional preprocessing, multi-preprocessing (MP) with 5 range, MP with 3 range, genetic algorithm, and successive projection algorithm. Limit of detection (LOD) and quantification (LOQ) were calculated using the best-performing model among five different PLSR models for HHV in kJ/kg, as well as the weight percentage (wt.%) of carbon (C), oxygen (O), hydrogen (H), and nitrogen (N). The LOD and LOQ for HHV were calculated as 622.42 kJ/kg and 1886.13 kJ/kg, respectively. Additionally, LOD and LOQ for ultimate analysis parameters, including C, O, H, and N were calculated as: 3.24 weight percentage (wt.%) and 9.81 wt.% for C, 2.04 wt.% and 6.18 wt.% for O, 0.35 wt.% and 1.05 wt.% for H, and 0.22 wt.% and 0.68 wt.% for N. The LOD and LOQ values for HHV, C, O, and H were lower than the minimum reference values used for model development, demonstrating the models’ high sensitivity and potential to reliably detect and precisely quantify these parameters. However, the LOD and LOQ values exceeded the minimum reference value used during model development for the N, indicating that the selected models have certain limitations in assessing the N content in biomass. The sample range should be expanded for wt.% of N to enhance the model’s performance, surpassing the LOD and LOQ values. This will improve the overall sensitivity of the model for reliable detection and quantification of N content in biomass samples.

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