•Calorific value prediction for unstudied biomass species.•Use of only two parameters of ultimate analysis is optimal.•H and S contents do not improve the prediction performance.
Higher heating value ...(HHV) and lower heating value (LHV) of 39 biomass species that include woody samples, herbaceous materials, agricultural residues, juice pulps, nut shells, etc. were predicted based on elemental analysis results. Simple linear equations were developed in which C, H, N, S, and O contents exist and the prediction performance of these empirical equations was evaluated comparing the experimental and the predicted values of calorific values according to the criteria of mean absolute error (MAE), average absolute error (AAE), and average bias error (ABE). For this purpose, equations that include parameters changing from only C to sum of C, H, N, S, and O were tested to compare the prediction performance of each additional parameter. It was concluded that, the use of only two parameters including carbon and extra one element either nitrogen or oxygen is optimal to predict the calorific value. These condensed forms of ultimate analysis-based equations gave r2 values changing in the range of 0.9219–0.9572. Improving effects of additional parameters are rather limited and the addition of H and S contents did not lead so significant improvement in prediction performance.
Densification is a technique used to improve biomass quality in wood pellet manufacturing and torrefaction treatment. In this study, the effects of torrefaction on the quality of Calliandra wood ...pellets were investigated, and pellets of Calliandra wood (Calliandra calothyrsus) and bark were evaluated. The study was conducted using a completely randomized design with two treatment factors, namely torrefaction temperature (250℃ and 300℃) and torrefaction duration (30, 45, and 60 min). The results showed that the interaction between temperature and torrefaction duration significantly affected the compressive strength, proximate value, and calorific value of the torrefied Calliandra wood pellets. An increase in the temperature and torrefaction duration decreased the compressive strength, moisture content, volatile matter content, and ash content of the torrefied Calliandra wood pellets. Conversely, the calorific value of Calliandra wood pellets increased with increasing temperature and torrefaction duration. The best-quality Calliandra wood pellets were produced at a torrefaction temperature and duration of 300℃ and 60 min, respectively. In terms of important quality parameters, ash content of 0.90% and calorific value of 6,303.80 cal/g were observed, which complied with the quality standards of Indonesian National Standard 8675:2018 and Deutsche Industrie Norm 51731.
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•Oxy-fuel combustion of oil–water emulsions with water contents of up to 75 wt%.•Oxygen enriched combustion of coal-water slurry from pyrolytic carbon black.•Thermal efficiencies of ...45% and higher at an exhaust gas temperature of 1100 °C.•Successful combustion with oxygen enrichments between 50 and 100 vol.%.•A pronounced water content resulted in a flameless oxy-fuel combustion.
In this study, a high-temperature combustion chamber was fueled with oil-water-emulsions (OWE) and coal-water-slurry (CWS) from pyrolytic carbon black in order to experimentally examine the feasibility of co-processing low-calorific value fuels in industrial high-temperature applications by using pure oxygen as oxidizer. The present paper is the first report on the oxy-fuel combustion characteristics of liquid fuels with a pronounced water content including flame characteristics, temperature distribution, thermal output and emission measurements in a semi-industrial combustion chamber at a thermal input of 300 kW and ambient pressure. The obtained results demonstrated the beneficial character of oxy-fuel combustion and showed that co-processing of OWE and CWS from pCB with pronounced water contents is technically feasible. A stable oxy-fuel combustion of OWE was achieved with water contents of up to 75 wt%. In addition, a successful combustion of CWS with a water content of 65 wt% and oxygen concentrations above 50 vol.% was observed. The obtained results further demonstrated the beneficial character of oxy-fuel combustion of OWE and CWS especially with regard to reduced NOx emissions. The combustion of OWE with a water content of 75 wt% resulted in a significant reduction of the NOx concentration compared to pure heating oil, namely from 760 to 110 ppm, whereas the maximum temperature of the combustion chamber decreased only slightly, while in the case of CWS combustion, the concentration of CO emitted decreased significantly from 34 to 9 ppm by increasing the oxygen concentration in the oxidizer from 50 to 100 vol.%.
•Valorization of apple skins was achieved by recovery of high added value molecules.•Response surface modeling was used for MAE optimization.•By the optimization a TP four times higher than in our ...previous work was obtained.•High calorific value (25 MJ/kg) of the exhausted solid after the extraction process.
Apple processing industry can be improved by the valorization of its residues. Apple skins could be used for the recovery of high added value compounds for the formulation of new antioxidant products (dietary supplements, cosmetics, drugs). In this study, apple skins from Jonagold cultivar were selected as raw material for an optimization study on microwave-assisted process parameters, using green solvents and an inert atmosphere combined to hard operating conditions (long time and high temperature), with the aim to enhance the mass transfer in the extraction process without significant loss in biomolecule activity. Response surface modeling was employed for the experimental planning and multi-variable process optimization. The effect of time, temperature and solvent composition on extraction performances and exhausted solid elemental composition were evaluated. The extract obtained after optimization showed very high extraction yields (50.4 mggallic acid equivalents/gdry biomass; 13.9 mgcatechin equivalents/gdry biomass) and remarkable antiradical properties. Moreover, after the extraction the solid residue exhibited higher carbon content (52.7%) and calorific value (24.6 MJ/kg) than the untreated apple skins.
The heating furnace is a sizeable energy-consuming device in iron and steel industry. In compact strip production (CSP), the size of the heating furnace is large, and the working conditions are ...complicated. Furthermore, the large fluctuation of furnace temperature leads to large loss of billet combustion and energy consumption. This article deals with the design of hybrid intelligent control based on condition identification for the combustion process of the CSP heating furnace. By analyzing the process of the heating furnace and existing problems, the structure of a hybrid intelligent control system is proposed, and the working conditions are divided into two categories: stable and fluctuating. A fuzzy controller is designed to improve the control accuracy of furnace temperature under the stable working condition, and an expert controller is used to adjust the temperature rapidly under the fluctuating working condition. Besides, calorific value compensation is introduced to reduce the influence of calorific value of gas fluctuation on temperature. After verifying the effectiveness, the proposed method has been used in a steel plant and achieved a good control result. The intelligent control system improves the control precision of the furnace temperature and reduces energy consumption compared with the traditional control system.
New prediction models based on wavelet neural networks (WNNs) have been proposed to estimate the gross calorific value (GCV) of coals. The input sets for the prediction models are involved of the ...proximate and ultimate analysis components of coal and the oxide analyses of ash. The coal samples, which have been employed to develop and verify the prediction models, are from United States Geological Survey (USGS) and China Huaneng Group. Some published methods have also been employed and redeveloped to make a comparison with the models proposed in this paper. The comparison reveals that the WNN models proposed here based on the proximate (ultimate) analysis components of coal, are consistently better than the published ones. The WNN models based on the oxide analyses of ash have higher accuracy in estimating the GCV of Chinese coals than US coals. Here we also analyze the possible reasons that could lead to the low estimated accuracy.
•Properties of US coal were studied for the prediction of gross calorific value (GCV).•Random forest (RF) models indicated that RF can accurately predict GCV.•RF models are much suitable to assess ...complicated relationships in coal processing.•Results recommended random forest as a model can be applied for other coal resources.
The last decade has witnessed of increasing the application of random forest (RF) models that are known as an exhibit good practical performance, especially in high-dimensional settings. However, on the theoretical side, their predictive ability markedly remains unexplained, especially in coal preparation. RF as a predictive model can tend to work well with large dimensional databases and rank predictors through its inbuilt variable importance measures. In this study, relationships among ultimate and proximate analyses of 6339 US coal samples from 26 states with gross calorific value (GCV) have been investigated by multivariable regression (MVR) and random forest (RF) models. RF method has been used for the variable importance. Models have shown that the ultimate analysis parameters are the most suitable estimators for GCV and that RF can predict GCV quite satisfactory. Running of the best arranged RF structures for the input sets and assessment of errors have suggested that RF models are suitable for complicated relationships.
To use natural gas as a feedstock alternative to coal and oil, its main constituent, methane, needs to be isolated with high purity1. In particular, nitrogen dilutes the heating value of natural gas ...and is, therefore, of prime importance for removal2. However, the inertness of nitrogen and its similarities to methane in terms of kinetic size, polarizability and boiling point pose particular challenges for the development of energy-efficient nitrogen-removing processes3. Here we report a mixed-linker metal-organic framework (MOF) membrane based on fumarate (fum) and mesaconate (mes) linkers, Zr-fum67-mes33-fcu-MOF, with a pore aperture shape specific for effective nitrogen removal from natural gas. The deliberate introduction of asymmetry in the parent trefoil-shaped pore aperture induces a shape irregularity, blocking the transport oftetrahedral methane while allowing linear nitrogen to permeate. Zr-fum67-mes33-fcu-MOF membranes exhibit record-high nitrogen/methane selectivity and nitrogen permeance under practical pressures up to 50bar, removing both carbon dioxide and nitrogen from natural gas. Techno-economic analysis shows that our membranes offer the potential to reduce methane purification costs by about 66% for nitrogen rejection and about 73% for simultaneous removal of carbon dioxide and nitrogen, relative to cryogenic distillation and amine-based carbon dioxide capture.
•Complex oscillatory dynamics are studied with unsteady perfectly stirred reactor.•Combustion stabilities are revealed with chemical explosive mode analysis.•The effects of gas composition and fuel ...blending are investigated.•Optimal fuel switching temperature, switching scheme are revealed.
The effective and efficient utilization of byproduct fuels has gained increasing attention in all industrial fields. In this study, flame stabilization mechanisms for non-standard low-calorific value (NLCV) gases of blast furnace gas and coke oven gas have been systematically analyzed under practical operating conditions of hot air heaters. The complex oscillatory dynamics has been successfully reproduced with the unsteady perfectly stirred reactor combustion model. The differences in the combustion stabilities between NLCV gases have been further revealed, with the kinetic importance of individual variable and chemical reaction for the complex dynamics being quantified with chemical explosive mode analysis. Then the effects of gas composition and fuel blending on combustion instability are investigated. The optimal fuel switching temperature, switching schemes and oscillating combustion inhibition methods are finally proposed for stable combustion of blast furnace gas and coke oven gas. The tolerance range of flow rate fluctuations are increased by 10% and 30% with selecting fuel switching scheme and initial combustion state reasonably.
