Investigating the characteristics of biomass wastes via particle feeder in downdraft gasifier.

Particle feeding plays a crucial role in the gasifier due to its effects on the efficiency and performance metrics of the thermochemical process. Investigating particle size distribution's impact on downdraft gasification reactor performance, this study delves into the significance of feedstock characteristics (moisture, volatile matter, fixed carbon, and ash contents) during the particle feeding stage. Various biomass wastes (date palm waste, olive pomace and sewage sludge) at diverse compositions and sizes are subjected to empirical determination of mass flow rates (MFR), power ratings, and storage times for each feedstock. The preheating process in the gasifier is considered, employing both an approximation and analytical solution. In addition, the influence of the equivalence ratio (ER) on the syngas yield is analyzed. The collected data reveals that for average particle size of 200 µm, the highest MFR (in g/min) are 0.518 ± 0.033, 7.691 ± 0.415, and 16.111 ± 1.050, for palm wood biomass, olive pomace and sewage sludge, respectively. Smaller particles (80 µm) led to extended storage times. Moreover, the lumped capacitance approximation method consistently underestimates preheating time, with a percentage error of 6.26%-17.08%. Response surface methodology (RSM) optimization analysis provides optimal gasification conditions for palm wood biomass, olive pomace, and sewage sludge with maximum cold gas efficiencies (CGEs) of 58.01%, 63.29%, and 52.27%. The peak conversion was attained at gasification temperatures of 1089.83 °C, 1151.93 °C, and 1102.91 °C for palm wood biomass, olive pomace, and sewage sludge, respectively. In addition, gasification equilibrium model determined optimal gasification temperatures as 1150 °C for palm biomass, 1200 °C for olive pomace, and 1150 °C for sewage sludge with respective syngas efficiencies of 59.62%, 64.13%, and 53.66%. Consequently, the examination of the dosing procedure, preheating dynamics, particle dimensions, ER, storage time, and their combined impacts offer practical insights to effectively control downdraft gasifiers in handling a variety of feedstocks.

Artificial neural network-assisted thermogravimetric analysis of thermal degradation in combustion reactions: A study across diverse organic samples.

During gasification the kinetic and thermodynamic parameter depend on both the feedstock and the process conditions. As a result, one needs to enhance the understanding of how to model numerically these parameters using thermogravimetric analyzer. Consequently, there exists a pressing need to computationally devise gasification model that can efficiently account to thermodynamic and kinetic parameter from thermogravimetric data. In this study, we numerically model gasification process kinetic and thermodynamic parameters, which vary with feedstock and operational conditions. Our novel approach involves creating an ANN model in MATLAB using a carefully optimized 8-20-20-10-1 architecture. Based on thermogravimetric analyzer (TGA) data, this model uniquely predicts critical kinetic (activation energy, pre-exponential factor) and thermodynamic parameters (entropy, enthalpy, Gibbs free energy, ignition index, boiling temperature). Our ANN model, trained on over 80 diverse samples with the Levenberg-Marquardt algorithm, excels at prediction, with an MSE of 6.185e-6 and an R2 value exceeding 0.9996, ensuring highly accurate estimates. Based on time, temperature, heating rate, and elemental composition, it accurately predicts thermal degradation. The model can predict TGA curves for many materials, demonstrating its versatility. For instance, it accurately estimates the activation energy for pure glycerol at 73.84 kJ/mol, crude glycerol at 67.55 kJ/mol, 12.12 kJ/mol for coal, and 111.3 kJ/mol for wood. These results, particularly for Kissinger-validated glycerol, demonstrate the model's versatility and efficacy in various gasification scenarios, making it a valuable tool for thermochemical conversion studies.

Design of a multistage hybrid desalination process for brine management and maximum water recovery.

Hypersaline brine production from desalination plants causes huge environmental stress due to the untenable conventional discharge strategies. Particularly, brine production is expected to drastically increase in the coming few decades due to the increasing desalination capacity in attempts of forestalling water scarcity. Thereby, zero liquid discharge (ZLD) is a worth-considering solution for strategic brine management. ZLD or minimal liquid discharge (MLD) systems provide maximum water recovery with least or zero liquid waste generation and valuable salt production. In this work, a theoretical design of ZLD/MLD system is proposed for reverse osmosis (RO) brine management. Different scenarios are investigated utilizing multistage freeze desalination (FD) and its hybridization with multistage direct contact membrane distillation (DCMD), and eutectic freeze crystallization (EFC) technologies. The design is based on the experimental assessment of the indirect FD process at different feed salinities, i.e., 2 g/L to 155 g/L. FD experiments showed that ice quality is reduced at greater crystallinity levels and initial concentration. Moreover, a computational fluid dynamics (CFD) model is utilized to assess the performance of DCMD. A single DCMD module could produce 53 kg/(m2.h) of pure water operating with 69% thermal efficiency. Eventually, water recovery, water quality, as well as specific energy consumption (SEC) are evaluated for the whole system. Based on different configurations of the hybrid ZLD system, the proposed design can achieve water recovery between 40 and 93% with SEC range of 28-114 kWh/m3. Results also showed that the produced water quality exceeds drinkable water standards ( ≪ 500 mg/L). This work has provided great evidence in the practicality of ZLD/MLD systems for sustainable brine management.

Response surface methodology approach for optimizing the gasification of spent pot lining (SPL) waste materials.

This paper presents new results on the gasification of spent pot lining (SPL) waste material generated in the primary aluminium smelting industry. The main objective is to test the performance of the gasification process of treated SPL materials and to develop an optimization method to maximize the quality of syngas fuel. The novelty of this study is the development of statistical models to predict the syngas composition and the gasification performance indicators during the SPL waste materials thermal conversion process. Modelling and simulation analysis are performed to convert the SPL solid materials to syngas fuel. The percentage of hydrogen (H2) and carbon monoxide (CO) in the syngas fuel, the cold gasification efficiency (CGE) and the carbon conversion (CC) are determined. The response surface methodology (RSM) is used for the optimization of the performance of the gasification process. The effects of the input factors such as the temperature, the equivalence ratio and the steam to fuel ratio on the output variables (H2 and CO in the syngas, the CGE and the CC) are determined. The optimization results show that the optimized operating parameters to maximize the H2, CO, CGE and CC were T = 1200 °C, ER = 0.1 and SFR = 1.29, respectively. The optimum values for the H2, CO, CGE and CC were 37.2%, 22.2%, 79.75% and 97.7%, respectively. New correlations for the variation of the output variables versus the input factors are also presented.

Freeze desalination: Current research development and future prospects.

Desalination is the solution for water security in regions with insufficient resources. This comes at high energy cost and hence improving desalination technologies translate into huge saving. Freeze desalination (FD) is emerging as an attractive low energy and less corrosion alternative to provide the needed fresh water. The maturity of the heat driven cooling technology and solar cooling have given freeze desalination an additional momentum. This paper summarizes the latest research progress done on FD that continues to push this technology towards deployment. It gives an overview of the FD configurations and highlighting its pros and cons, presents the recent experimental work that investigate the physics of the technology, and reviews the latest high-fidelity numerical modeling of brine freezing and salt diffusion away from crystal lattice which taps on the advanced development in computational power and multiphysics integration. This enables one to identify the challenges facing FD technology and stating the prospect and foreseeable research. The finding suggests that direct and indirect FD have been evolved well while the indirect is becoming the mainstream method for risk avoidance, while vacuum freezing and eutectic freezing are still facing large obstacles in their application. For direct FD, gas hydrate combined with liquefied natural gas (LNG) regasification has been popular topics to reduce their desalination cost. Simulation and modeling development in indirect FD continue to improve the knowledge of the mechanism of ice growth and salt entrapment which are key problems that need further experimental and numerical investigations. Nonetheless, the current successful application of LNG cold energy in freeze desalination, the hybridization of FD with conventional desalination technologies, as well as ultrasound assisted freezing are promising directions for FD commercialization.

Combustion and emissions analysis of Spent Pot lining (SPL) as alternative fuel in cement industry.

Spent Pot lining (SPL) is a carbonaceous material generated during the primary aluminum smelting process. SPL is a hazardous waste but the high energy density (carbon rich fraction) and good environmental impacts (toxic materials such as cyanides are destroyed at temperature well above 1000 °C) of the treated SPL (water washed followed with and NaOH and H2SO4 treatments) makes it a valuable material for use as fuel feedstocks in cement and steel industries. The principal objective of this study is to investigate the combustion performance and emission characteristics of SPL as alternative fuel in cement industry. The goal is to develop sustainable process systems by using solid waste materials such as SPL from Aluminum industry as a fuel in the cement industry. The proximate (moisture, volatile, fixed carbon, and ash contents) and ultimate (C, H, O, N, S) analyses and the heating value (MJ/kg) of the raw and treated SPL materials are determined first. Computational Fluid Dynamics analysis based on gas and discrete phase modeling (DPM) approach and probability density function/mixture fraction turbulent non-premixed combustion model are used to test the combustion performance and pollutants emissions (flame temperature, fuel particle devolatization and burnout rates, and species concentration formations inside and at the exit of the combustor) of the SPL fuel. The results of the SPL or the alternative fuel combustion are compared with conventional fuel (coal) combustion used in cement industry. The final treated SPL fuel (water washed SPL followed with NaOH and H2SO4 treatments) combustion shows lower temperature and NO and CO2 emissions at the exit from the furnace compared to coal. The results show that the final treated fuel can be used as alternative fuel in cement industry to displace coal fuel and reduce the pollutant emissions from the combustor in cement industry.

Acousto-chemical analysis in multi-transducer sonochemical reactors for biodiesel production.

Biodiesel is a powerful alternative fuel that is less polluting and problematic to produce and implement. The production process of biodiesel also gives us the byproduct glycerol, which is a useful feedstock to produce hydrogen and syngas as fuels. With such high value as a fuel we are in need of better production technologies for biodiesel, which is currently being pursued through sonochemical reactors. The development of continuous sonochemical reactors for biodiesel production is a crucial requirement for the biofuel industry. Sonochemical reactors make use of ultrasound and acoustic cavitation to produce biodiesel from waste cooking oils (WCO). In this work we carried out both numerical simulation and experimental analysis of sonochemical reactors with multiple transducers. Through simulation, the effect of double vs a single transducer has been tested for a continuous flow sonochemical reactor. In experimental work three different cases with different ultrasound systems (bath, probe and bath+probe) have been tested. In both the studies, acoustic pressure and biodiesel conversion are analyzed. Results for the simulation show that in shorter reactors, the high cavitation from two transducers dampens the acoustic pressures leading to low conversion. However, at taller heights the effect of combined cavitation is less severe and the acoustic pressure and biodiesel yield are very similar between the designs having single and double transducers. From experiments it was found that the biodiesel conversion depends on several acoustic conditions mainly cavitation. A meticulous and insightful analysis was made to understand the difference in bath type and probe type ultrasound systems on acoustic pressure and biodiesel conversion.

Numerical simulation of waste tyres gasification.

Gasification is a thermochemical pathway used to convert carbonaceous feedstock into syngas (CO and H2) in a deprived oxygen environment. The process can accommodate conventional feedstock such as coal, discarded waste including plastics, rubber, and mixed waste owing to the high reactor temperature (1000 °C-1600 °C). Pyrolysis is another conversion pathway, yet it is more selective to the feedstock owing to the low process temperature (350 °C-550 °C). Discarded tyres can be subjected to pyrolysis, however, the yield involves the formation of intermediate radicals additional to unconverted char. Gasification, however, owing to the higher temperature and shorter residence time, is more opted to follow quasi-equilibrium and being predictive. In this work, tyre crumbs are subjected to two levels of gasification modelling, i.e. equilibrium zero dimension and reactive multi-dimensional flow. The objective is to investigate the effect of the amount of oxidising agent on the conversion of tyre granules and syngas composition in a small 20 kW cylindrical gasifier. Initially the chemical compositions of several tyre samples are measured following the ASTM procedures for proximate and ultimate analysis as well as the heating value. The measured data are used to carry out equilibrium-based and reactive flow gasification. The result shows that both models are reasonably predictive averaging 50% gasification efficiency, the devolatilisation is less sensitive than the char conversion to the equivalence ratio as devolatilisation is always complete. In view of the high attained efficiency, it is suggested that the investigated tyre gasification system is economically viable.