• Energy Research

Co-torrefaction is a flexible way of improving the properties of various kinds of waste biomass for utilization as a clean solid fuel. Rice straw (RS) and medium density fiberboard (MDF) were used as feedstock for the torrefaction. Three input parameters were evaluated to determine the optimum conditions: rice straw ratio (RSR), torrefaction temperature and residence time. A response surface method based on a Box-Benhken design was used to achieve the optimum conditions (maximizing torrefied heating value and energy yield). Main and interaction effects for the independent variables on the responses were investigated based on analysis of variance (ANOVA). The findings revealed that temperature was the main effect and that there was no interaction effect between the inputs. Thus, a lower temperature optimized co-torrefaction. The optimum conditions for maximizing the heating value (22.13 MJ/kg) and energy yield (99.60%) were an RSR of 25%, a temperature of 208.10 °C and a residence time of 50 min. The experimental values were in good agreement with the corresponding predicted values. These findings should provide guidelines for the thermal pretreatment of mixed waste material for co-firing or co-gasification.

Abstract Exergy analysis was performed to evaluate the gasification process of torrefied biomass. The rice husk pellets (RHP) were employed as the feedstock in this paper. Two batches of RHP were torrefied for 1 h before gasification. One batch was at 250 °C and the other one was at 350 °C. Gasification was conducted in a 30 kWth bubbling fluidized bed. The effects of air equivalence ratio (ER) and torrefaction temperature on overall exergy efficiency were examined in this paper. Results of experiments showed that torrefaction process may raise chemical energy (exergy) of RHP due to lower values of O/C and H/C. However, the overall energy efficiency decreases due to the energy loss in volatile gas and electric energy input during the combined torrefaction-gasification process. The efficiency decrease was more severe for the case of torrefaction at 350 °C. The overall exergy efficiencies of the torrefied RHP at 250 °C and 350 °C are 30% and 21%, respectively.

Due to the COVID-19 pandemic, large amounts of medical wastes have been produced and their disposal has resulted in environmental and human health problems. This medical waste may include face masks, gloves, face shields, goggles, coverall suits, and other related wastes, such as hand sanitizer and disinfectant containers. To address this issue, the effect was investigated of gasification process parameters (type of COVID-19 medical mask based on the polypropylene ratio, pressure, steam ratio, and temperature) on hydrogen syngas and cold gas efficiency. The gasification model was developed using process modeling based on the Aspen Plus software. Response surface methodology with a 3(k) statistical factorial design was used to optimize the process aiming for the highest hydrogen yield and cold gas efficiency. Analysis of variance showed that both the steam ratio and temperature were significant parameters regarding the hydrogen yield and cold gas efficiency. Proposed models were constructed with very high accuracy based on their coefficient of determination (R(2)) values being greater than 0.97. The optimum conditions were: 65 % polypropylene in the mixture, a pressure of 1 bar, a steam ratio of 0.38, and a temperature of 900 °C, producing a maximum hydrogen yield of 40.61 % and cold gas efficiency of 81.43 %. These results supported the efficacy of the primary design for steam gasification using a mixture of plastic wastes as feedstock. The hydrogen could be utilized in chemical applications, whereas the efficiency could be used as a basis for further development of the process.

Torrefaction is a remarkable technology in biomass-to-energy. However, biomass has several disadvantages, including hydrophilic properties, higher moisture, lower heating value, and heterogeneous properties. Many conventional approaches, such as kinetic analysis, process modeling, and computational fluid dynamics, have been used to explain torrefaction performance and characteristics. However, they may be insufficient in actual applications because of providing only some specific solutions. Machine learning (ML) and statistical approaches are powerful tools for analyzing and predicting torrefaction outcomes and even optimizing the thermal process for its utilization. This state-of-the-art review aims to present ML-assisted torrefaction. Artificial neural networks, multivariate adaptive regression splines, decision tree, support vector machine, and other methods in the literature are discussed. Statistical approaches (SAs) for torrefaction, including Taguchi, response surface methodology, and analysis of variance, are also reviewed. Overall, this review has provided valuable insights into torrefaction optimization, which is conducive to biomass upgrading for achieving net zero.

Coffee silver skin, an organic residue from coffee production, demonstrates low solid fuel characteristics such as low bulk density and heating value, necessitating enhancements for solid fuel applications. Torrefaction in a flue gas environment (5% O2, 15% CO2, and a balance of N2, v/v) is more energy-efficient than inert torrefaction, using recovered flue gas to improve fuel quality and process efficiency. Three input factors were assessed: temperature (200, 250, and 300 °C), residence time (30, 45, and 60 min), and gas media (N2 and flue gas). Four performance metrics were evaluated: energy yield, upgrading energy index, specific energy consumption, and energy-mass co-benefit. Temperature significantly influenced most outcomes, except for energy-mass co-benefit, which was medium-dependent. Optimal torrefaction conditions achieving maximum energy yield (71.48%) and energy-mass co-benefit (5.30%) were identified at 200 °C for 30 min with flue gas. The torrefied material’s properties include moisture content, volatile matter, fixed carbon, and ash content of 3.03%, 69.24%, 27.04%, and 1.01%, respectively. Furthermore, the hydrophobicity of pelletized coffee silver skin notably increased under flue gas conditions, evident by a contact angle greater than 100°, indicating that flue gas torrefaction is a feasible approach for producing high-grade solid fuel.

Polymer-based heat exchangers can offer a promising solution for environmental sustainability due to their low energy consumption. The incorporation of microchannels and nanofluids further enhances the heat transfer performance of these heat exchangersIn this study, a polymer-based microchannel heat exchanger combined with nanofluid is simulated through the integration of an artificial neural network predictive model and a three-dimensional computational fluid dynamics model. This study unveils an advanced calculation that integrates artificial intelligence and readily-available computational software provided as the advanced calculation system. A statistical mathematics response surface method which data is used for correlating the calculation model is applied to obtain the design parameters between operating conditions and for optimal performance. The optimized results reveal that polymer-based microchannel heat exchanger combined with nanofluid is a promising innovation. The heat transfer improvement achieved a 12 % increase in the overall heat transfer coefficient by using TiO2/Water compared to Water. Moreover, a 1.03 performance index is obtained when CuO/Water nanofluid is used, a 66 horizontal parallel connecting of the polymer-based microchannel heat exchanger shows that the equipment can afford the same heat transfer performance of the metal-based microchannel heat exchanger in TiO2/Water nanofluid usage and implying a balance between heat transfer enhancement and energy consumption.

Experimental and computational studies have been conducted to predict the maximum and distributional temperatures in the battery pack with and without a copper foam layer utilizing a channel flow channel and ferrofluid as the coolant. A set of 60 Li-ion 18650 cylindrical batteries were put through their paces; each one had a voltage of 25.2V and a total current rating of 30Ah. The findings show that the copper foam significantly impacts the thermal cooling system. The increased mixing intensity of the coolant at the copper surface and region in the flow channel that contains the foam sheet improves heat transmission and ensures that the battery pack is consistently at a consistent temperature. With an average inaccuracy of 5.79 % for cooling battery model I and 4.95 % for cooling battery model II, the anticipated outcomes are in fair agreement with the outcomes expected. In Model I, which does not the copper foam, the pack may reach a maximum temperature of 27.4 °C, but in Model II, which has copper foam, it reaches 26.3 °C. As a crucial component of continuing research into different approaches to enhance thermal cooling and heat transfer for the purpose of achieving stable and safe operation, these findings are pertinent to the development of the cooling system using copper foam. This work has been conducted continuously, especially various charging and discharging C rates.

BACKGROUND AND OBJECTIVES: The needs of fuel pellets from varied feed stocks have opened up opportunities and challenges for pellets production from non-woody biomass. Wastes of plastic recycling and wood sawing contained a high potential for energy source and suited for pelletizing as a solid fuel. METHODS: The characteristics and combustion kinetics of fuel pellets made using a mixture of waste of polyethylene terephthalate and biomass (Tectona grandis Linn.f) with a polyethylene terephthalate to biomass ratio of 9:1. The investigation covered physico-chemical properties and their functional group analysis, heavy metal concentration and ionic leachability testing, and ash analysis. In this context, thermogravimetric analysis was used in an atmosphere of oxygen gas, over a temperature range of 50-800 °C and at different heating rates. The work ends with discussion of the kinetics study via three comparative evaluations and the feasibility of fuel pellets for energy utilization. FINDINGS: Pelletizing with this ratio (9:1) was present the durability of PET/biomass pellets, a uniform dimension, ease handling, storage, and transportation common as woody pellets. Some technical challenges such as low moisture content and high volatile matter content were feedstock dependent. The major characteristics were a combination of those from both the constituent materials. Functional groups of the pellets were contributed by terephthalate and lignocellulose. The addition of a small amount of biomass in pellets could improve their thermal decomposition behavior. The properties of the polyethylene terephthalate/biomass pellets indicated that were fit for combustion with a high heating value equal to 19.20 MJ/kg. Heavy metals and ionic contaminants were below the maximum limits of the standards because of the cleanliness of the raw materials. However, the minor effects of earth materials and a caustic soda detergent were resulted in the alteration of residue chemicals. The pellets had lower ignition, devolatilization, and burnout temperatures than the original polyethylene terephthalate waste; likewise, the peak and burnout temperatures shifted to a lower zone. The activation energy values obtained using the Kissinger-Akahira-Sunose, Ozawa-Flynn-Wall, and Starink models were similar and in the range 142–146 kJ/mol. CONCLUSION: These findings may provide crucial information on fuel pellets from blended polyethylene terephthalate/biomass to assist the design and operation of a co-combustion system with traditional solid fuels. Such modifications of fuel pellets suggest the possibility of operating in large-scale furnace applications and can further be upgraded to other fuels production via modern bioenergy conversion processes. ========================================================================================== COPYRIGHTS©2021 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.==========================================================================================