Many attempts have been made to estimate calorific value of bagasse using mathematical equations, which were created based on data from proximate, ultimate, physical and chemical analysis. Questions have been raised o...Many attempts have been made to estimate calorific value of bagasse using mathematical equations, which were created based on data from proximate, ultimate, physical and chemical analysis. Questions have been raised on the applicability of these equations in different parts of the globe. This study was initiated to tackle these problems and also check the most suited mathematical models for the Law Heating Value of Cameroonian bagasse. Data and bagasse samples were collected at the Cameroonian sugarcane factory. The effects of cane variety, age of harvesting, source, moisture content, and sucrose on the LHV of Cameroon bagasse have been tested. It was shown that humidity does not change within a variety, but changes from the dry season to the rainy season;the sugar in the rainy season is significantly different from that collected in the dry season. Samples of the same variety have identical LHV. LHV in the dry season is significantly different from LHV in the rainy season. According to the fact that this study was done for cane with different ages of harvesting, the maturity of Cameroonian sugarcane does not affect LHV of bagasse. Tree selected models are much superior tool for the prediction of the LHV for bagasse in Cameroon compared to others. The standard deviation of these validated models is around 200 kJ/kg compared to the experimental. Thus, the models determined in foreign countries, are not necessarily applicable in predicting the LHV of bagasse in other countries with the same accuracy as that in their native country. There was linear relationship between humidity, ash and sugar content in the bagasse. It is possible to build models based on data from physical composition of bagasse using regression analysis.展开更多
Great differences between municipal solid wastes (MSW) produced at different places and different times in terms of such parameters as physical ingredient and heating value lead to difficulty in effective handling of ...Great differences between municipal solid wastes (MSW) produced at different places and different times in terms of such parameters as physical ingredient and heating value lead to difficulty in effective handling of MSW. In this paper, ingredient, heating value and their temporal varying trends of typical MSW in Beijing were continuously measured and analyzed. With consideration of the process in pyrolysis and incineration, correlation between physical ingredients and heating values was induced, favorable for evaluation of heating value needed in handling of MSW from simple analysis of physical ingredients of it.展开更多
Ni-based catalysts supported by γ-Al_2O_3 were prepared for improving the lower heating value( LHV) of biomass gasification fuel gas through methanation. Prior to the performance tests, the physico-chemical propertie...Ni-based catalysts supported by γ-Al_2O_3 were prepared for improving the lower heating value( LHV) of biomass gasification fuel gas through methanation. Prior to the performance tests, the physico-chemical properties of the catalyst samples were characterized by N_2 isothermal adsorption/desorption, X-ray diffraction( XRD) and a scanning electron microscope( SEM). Afterwards, a series of experiments were carried out to investigate the catalytic performance and the results showthat catalysts with 15% and20% Ni loadings have better methanation catalytic effect than those with 5% and 10% Ni loadings in terms of elevating the LHV of biomass gasification fuel gas. M oreover, controllable influential factors such as the reaction temperature, the H_2/CO ratio and the water content occupy an important position in the methanation of biomass gasification fuel gas. 15 Ni/γ-Al_2O_3 and 20 Ni/γ-Al_2O_3 catalysts have a higher CO conversion and CH_4 selectivity at 350 ℃ and the LHV of biomass gasification fuel gas can be largely increased by 34. 3 % at 350 ℃. Higher H_2/CO ratio and a lower water content are more beneficial for improving the LHV of biomass gasification fuel gas when considering the combination of both CO conversion and CH_4 selectivity. This is due to the fact that a higher H_2/CO ratio and lower water content can increase the extent of the methanation reaction.展开更多
In order to know the character of the heat value control system, determine the influence of natural gas quality and flow on the heat value, and learn how to adjust the parameters of control system, the model of the wh...In order to know the character of the heat value control system, determine the influence of natural gas quality and flow on the heat value, and learn how to adjust the parameters of control system, the model of the whole system is established, and simulation of the system is adopted in Matlab/Simulink. The simulation result shows that the feedback system with feed-forward block controls the heat value very well, and the simulation result can effectively guide the engineering design of the heat value control system, and the efficiency of engineering is improved.展开更多
Biomass is a carbon-neutral renewable energy resource.Biochar produced from biomass pyrolysis exhibits preferable characteristics and potential for fossil fuel substitution.For time-and cost-saving,it is vital to esta...Biomass is a carbon-neutral renewable energy resource.Biochar produced from biomass pyrolysis exhibits preferable characteristics and potential for fossil fuel substitution.For time-and cost-saving,it is vital to establish predictive models to predict biochar properties.However,limited studies focused on the accurate prediction of HHV of biochar by using proximate and ultimate analysis results of various biochar.Therefore,the multi-linear regression(MLR)and the machine learning(ML)models were developed to predict the measured HHV of biochar from the experiment data of this study.In detail,52 types of biochars were produced by pyrolysis from rice straw,pig manure,soybean straw,wood sawdust,sewage sludge,Chlorella Vulgaris,and their mixtures at the temperature ranging from 300 to 800℃.The results showed that the co-pyrolysis of the mixed biomass provided an alternative method to increase the yield of biochar production.The contents of ash,fixed carbon(FC),and C increased as the incremental pyrolysis temperature for most biochars.The Pearson correlation(r)and relative importance analysis between HHV values and the indicators derived from the proximate and ultimate analysis were carried out,and the measured HHV was used to train and test the MLR and the ML models.Besides,ML algorithms,including gradient boosted regression,random forest,and support vector machine,were also employed to develop more widely applicable models for predicting HHV of biochar from an expanded dataset(total 149 data points,including 97 data collected from the published literature).Results showed HHV had strong correlations(|r|>0.9,p<0.05)with ash,FC,and C.The MLR correlations based on either proximate or ultimate analysis showed acceptable prediction performance with test R2>0.90.The ML models showed better performance with test R^(2)around 0.95(random forest)and 0.97–0.98 before and after adding extra data for model construction,respectively.Feature importance analysis of the ML models showed that ash and C were the most important inputs to predict biochar HHV.展开更多
In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fu...In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.展开更多
The characteristics of fuel from biomass, coal and some waste materials are lower heat value and different compositions. The lower heat value fuel (LHVF) can be used on power engine such as boiler, gas engine and gas ...The characteristics of fuel from biomass, coal and some waste materials are lower heat value and different compositions. The lower heat value fuel (LHVF) can be used on power engine such as boiler, gas engine and gas turbine. Some laboratory and pilot work have been done, but the work done on micro-gas turbine is still limited. The characteristics of LHVF can cause the operations change of micro-gas turbine designed for nature gas. Some possible adjustment and modification methods were mentioned for the use of LHVF on micro-gas turbine. One kind of representative LHVF was chosen and the operations of micro-gas turbine were analyzed. The temperature field and the non-uniformity scale of temperature distribution of combustor were calculated using FLUENT. The feasibility of different adjustment and modification methods were analyzed according to the efficiency, output power and the non-uniformity scale of temperature distribution.展开更多
Heat-treated wood has good dimensional stability,corrosion resistance and visual quality,but it is prone to mold,which limits its application.Based on the pH value of heat-treated wood,this study examines the factors ...Heat-treated wood has good dimensional stability,corrosion resistance and visual quality,but it is prone to mold,which limits its application.Based on the pH value of heat-treated wood,this study examines the factors affecting the pathogenesis causing heat-treated wood mold.Normally,the pH value of the heat-treated wood is between 4.38 and 5.10,which is suitable for the growth of mold.However,the pH of the heat-treated copper-containing material is between 6.63 and 7.12,which deviates the treated wood from the comfortable growth conditions for the mold,thereby reducing the occurrence of mold.展开更多
Based on thermal value theory, the aim of this paper is to deduce the theoretical formulas for evaluating the energy effective utilization degree in technological pyrological processes exemplified by metallurgical hea...Based on thermal value theory, the aim of this paper is to deduce the theoretical formulas for evaluating the energy effective utilization degree in technological pyrological processes exemplified by metallurgical heating furnaces. Heat transfer models for continuous heating furnaces, batch-type heating furnaces, and regenerative heating furnaces are established, respectively. By analyzing the movement path of injected infinitesimal heat attached on steel or gas, thermal value equations of continuous, batch-type, and regenerative heating furnaces are derived. Then the influences of such factors as hot charging, gas preheating and intake time of heat on energy effective utilization degree are discussed by thermal value equations. The results show that thermal value rises with hot charging and air preheating for continuous heating furnaces, with shorter intake time when heat is attached on steel or longer intake time when heat is attached on gas for batch-type heating furnaces and that with more heat supply at early heating stage or less at late stage for regenerative heating furnaces.展开更多
In recent decades,the generation of Municipal Solid Waste(MSW)is steadily increasing due to urbanization and technological advancement.The col-lection and disposal of municipal solid waste cause considerable environme...In recent decades,the generation of Municipal Solid Waste(MSW)is steadily increasing due to urbanization and technological advancement.The col-lection and disposal of municipal solid waste cause considerable environmental degradation,making MSW management a global priority.Waste-to-energy(WTE)using thermochemical process has been identified as the key solution in this area.After evaluating many automated Higher Heating Value(HHV)predic-tion approaches,an Optimal Deep Learning-based HHV Prediction(ODL-HHVP)model for MSW management has been developed.The objective of the ODL-HHVP model is to forecast the HHV of municipal solid waste,based on its oxy-gen,water,hydrogen,carbon,nitrogen,sulphur and ash constituents.In addition,the ODL-HHVP model contains a Deep Support Vector Machine(DSVM)regres-sion component that can accurately predict the HHV.In addition,the Beetle Swarm Optimization(BSO)method is utilised as a hyperparameter optimizer in conjunction with the DSVM model,resulting in the highest HHV prediction accu-racy.A comprehensive simulation study is conducted to validate the performance of the ODL-HHVP method.The Multiple Linear Regression(MLR),Genetic Pro-gramming(GP),Resilient backpropagation(RP),Levenberg Marquardt(LM)and DSVM approaches have attained an ineffective result with RMSEs of 4.360,2.870,3.590,3.100 and 3.050,respectively.The experimentalfindings demon-strate that the ODL-HHVP technique outperforms existing state-of-art technolo-gies in a variety of respects.展开更多
In this paper,a compact difference scheme is established for the heat equations with multi-point boundary value conditions.The truncation error of the difference scheme is O(τ2+h^4),where t and h are the temporal ste...In this paper,a compact difference scheme is established for the heat equations with multi-point boundary value conditions.The truncation error of the difference scheme is O(τ2+h^4),where t and h are the temporal step size and the spatial step size.A prior estimate of the difference solution in a weighted norm is obtained.The unique solvability,stability and convergence of the difference scheme are proved by the energy method.The theoretical statements for the solution of the difference scheme are supported by numerical examples.展开更多
With more ready-to-eat foods and increased shelf-lives, prevention of Listeria monocytogenes contamination has become a necessity for the food industry. This study examined the effects of sublethal heat treatment on t...With more ready-to-eat foods and increased shelf-lives, prevention of Listeria monocytogenes contamination has become a necessity for the food industry. This study examined the effects of sublethal heat treatment on the decimal reduction time (D-values) of three L. monocytogenes serotypes (1/2a, 1/2b, 4c), and non-pathogenic L. innocua. The D70 (D-value at 70℃) values of heat-shocked (HS) and non-heat-shocked (NHS) Listeria grown in tryptic soy broth (TSB) were determined. The D70 values of HS L. monocytogenes serotype 1/2a and L. innocua were significantly higher compared to NHS cultures, although by 48 h, the values returned to NHS levels. When HS and NHS 1/2a and 1/2b were inoculated on crab meat and cooked shrimp, the D70 values of HS cultures were at least 2-fold higher, compared to when they were grown in TSB. This increase in heat resistance for the HS cultures may be attributed to the protective effect of the seafood matrix itself.展开更多
This work investigated and quantified the calorific values of the main branches and trunks of eleven (11) tropical trees in correlation with their chemical composition in order to assess their suitability for use as c...This work investigated and quantified the calorific values of the main branches and trunks of eleven (11) tropical trees in correlation with their chemical composition in order to assess their suitability for use as credible sources of wood fuel. The determination of the carbon, hydrogen, nitrogen, oxygen and sulphur (CHNOS) content of the samples was done using an organic elemental analyser, while an oxygen bomb calorimeter was used to experimentally determine their corresponding gross heat values. The experimental gross heat values for the branches examined ranged from 18,703.37 kJ/kg in Lophira lanceolata to 21,350.35 kJ/kg in Afzelia africana while that of the trunks ranged from 19,747.74 kJ/kg in Tectonia grandis to 22,408.68 kJ/kg in Prosopis africana. These values were within and about the expected ranges observed for tropical trees and may be considered adequate for wood fuel. The general trend in both branches and trunks was that the higher the carbon content, the higher the gross heat value of sample. The absence of sulphur in almost all the samples except, Prosopis africana, (0.055%) was indicative of the fact that the negative environmental impact with respect to harmful emissions of oxides of sulphur is practically non-existent with respect to these species. In the light of the aforementioned variables, the main branches of Afzelia africana (21,350.35 kJ/kg), Nauclea diderrichii (21,157.30 kJ/kg) and Tectonia grandis (20,257.13 kJ/kg) could be used as credible sources of firewood and charcoal production. With respect to the trunks, the timbers in order of preference would ideally be Prosopis africana (22,408.68 kJ/kg), Nauclea diderichii (21,436.42 kJ/kg) and Brachstigia eurychoma (20,924.7 kJ/kg).展开更多
This paper deals with the effect of microwave energy for mullite formation from placer sillimanite. A mullite formation is seen when 60 % SiC and 5% binder are used with the composite charge material, i.e. sillimanite...This paper deals with the effect of microwave energy for mullite formation from placer sillimanite. A mullite formation is seen when 60 % SiC and 5% binder are used with the composite charge material, i.e. sillimanite (60%) and Al2O3 (40%). The maximum temperature of the microwave sintering furnace achieved is 1355°C at 2450 W microwave power. Addition of 10 % binder to the same charge material with 60% SiC, the furnace temperature achieved is 1384°C at microwave power 1900 W. Mullite is formed within 25 minutes from the sillimanite, under the above experimental conditions. Whereas under the similar additive conditions, the mullite formed from sillimanite in conventional furnace heating, it took 3 hours at 1300°C. XRD data show the mullite phase for both the products obtained from microwave sintering furnace and conventional furnace. FESEM image analysis shows the mullite formations, SiC fibrous cluster and alumina needles in microwave treated sample. Thus microwave heat source is much more effective for value addition to red sediment placer sillimanite to form mullite in compare to conventional furnace.展开更多
In this paper we study inviscid and viscid Burgers equations with initial conditions in the half plane . First we consider the Burgers equations with initial conditions admitting two and three shocks and use the HOPF-...In this paper we study inviscid and viscid Burgers equations with initial conditions in the half plane . First we consider the Burgers equations with initial conditions admitting two and three shocks and use the HOPF-COLE transformation to linearize the problems and explicitly solve them. Next we study the Burgers equation and solve the initial value problem for it. We study the asymptotic behavior of solutions and we show that the exact solution of boundary value problem for viscid Burgers equation as viscosity parameter is sufficiently small approach the shock type solution of boundary value problem for inviscid Burgers equation. We discuss both confluence and interacting shocks. In this article a new approach has been developed to find the exact solutions. The results are formulated in classical mathematics and proved with infinitesimal technique of non standard analysis.展开更多
Higher heating value(HHV)is the key parameter for replacing Refuse-Derived Fuel(RDF)with fossil fuels in the cement industry.HHV can be measured with a bomb calorimeter or predicted from direct elemental data by using...Higher heating value(HHV)is the key parameter for replacing Refuse-Derived Fuel(RDF)with fossil fuels in the cement industry.HHV can be measured with a bomb calorimeter or predicted from direct elemental data by using regression models.Both methods require the continuous use of special laboratory equipment and are time consuming.To overcome these limitations,this study aims to predict the HHV value of RDF from predicted elemental data by using regression models.Therefore,once the predicted elemental data are generated,there will be no need to have continuous elemental data to predict HHV.Predicted elemental data were generated from direct elemental data and Near Infrared(NIR)camera-based spectrometric data by using a deep learning model.A convolutional neural networks(CNN)model was used for deep learning and was trained with 10,500 NIR image samples,each of which was 28×28×1.Different regression models(Linear,Tree,Support-Vector Machine,Ensemble and Gaussian process)were applied for HHV prediction.According to these results,higher R2 values(>0.85)were obtained with Gaussian process models(except for the Rational Quadratic model)for the predicted elemental data.Among the Gaussian models,the highest R2(0.95)but the lowest Root Mean Square Error(RMSE)(0.0563),Mean Squared Error(MSE)(0.0317)and Mean Absolute Error(MAE)(0.0431)were obtained with the Mattern 5/2 model.The results of predictions from predicted elemental data were compared to predictions from direct elemental data.The results show that the regression from predicted elemental data has an adequate prediction(R2=0.95)compared to the prediction from the direct elemental data(R^(2)=0.99).展开更多
文摘Many attempts have been made to estimate calorific value of bagasse using mathematical equations, which were created based on data from proximate, ultimate, physical and chemical analysis. Questions have been raised on the applicability of these equations in different parts of the globe. This study was initiated to tackle these problems and also check the most suited mathematical models for the Law Heating Value of Cameroonian bagasse. Data and bagasse samples were collected at the Cameroonian sugarcane factory. The effects of cane variety, age of harvesting, source, moisture content, and sucrose on the LHV of Cameroon bagasse have been tested. It was shown that humidity does not change within a variety, but changes from the dry season to the rainy season;the sugar in the rainy season is significantly different from that collected in the dry season. Samples of the same variety have identical LHV. LHV in the dry season is significantly different from LHV in the rainy season. According to the fact that this study was done for cane with different ages of harvesting, the maturity of Cameroonian sugarcane does not affect LHV of bagasse. Tree selected models are much superior tool for the prediction of the LHV for bagasse in Cameroon compared to others. The standard deviation of these validated models is around 200 kJ/kg compared to the experimental. Thus, the models determined in foreign countries, are not necessarily applicable in predicting the LHV of bagasse in other countries with the same accuracy as that in their native country. There was linear relationship between humidity, ash and sugar content in the bagasse. It is possible to build models based on data from physical composition of bagasse using regression analysis.
基金The Key Projects of Chinese Academy of Sciences(No.KY95T-03-02)the National Natural Science Foundation of China(No.59776023)
文摘Great differences between municipal solid wastes (MSW) produced at different places and different times in terms of such parameters as physical ingredient and heating value lead to difficulty in effective handling of MSW. In this paper, ingredient, heating value and their temporal varying trends of typical MSW in Beijing were continuously measured and analyzed. With consideration of the process in pyrolysis and incineration, correlation between physical ingredients and heating values was induced, favorable for evaluation of heating value needed in handling of MSW from simple analysis of physical ingredients of it.
基金The International S&T Cooperation Program of China(No.2014DFE70150)
文摘Ni-based catalysts supported by γ-Al_2O_3 were prepared for improving the lower heating value( LHV) of biomass gasification fuel gas through methanation. Prior to the performance tests, the physico-chemical properties of the catalyst samples were characterized by N_2 isothermal adsorption/desorption, X-ray diffraction( XRD) and a scanning electron microscope( SEM). Afterwards, a series of experiments were carried out to investigate the catalytic performance and the results showthat catalysts with 15% and20% Ni loadings have better methanation catalytic effect than those with 5% and 10% Ni loadings in terms of elevating the LHV of biomass gasification fuel gas. M oreover, controllable influential factors such as the reaction temperature, the H_2/CO ratio and the water content occupy an important position in the methanation of biomass gasification fuel gas. 15 Ni/γ-Al_2O_3 and 20 Ni/γ-Al_2O_3 catalysts have a higher CO conversion and CH_4 selectivity at 350 ℃ and the LHV of biomass gasification fuel gas can be largely increased by 34. 3 % at 350 ℃. Higher H_2/CO ratio and a lower water content are more beneficial for improving the LHV of biomass gasification fuel gas when considering the combination of both CO conversion and CH_4 selectivity. This is due to the fact that a higher H_2/CO ratio and lower water content can increase the extent of the methanation reaction.
文摘In order to know the character of the heat value control system, determine the influence of natural gas quality and flow on the heat value, and learn how to adjust the parameters of control system, the model of the whole system is established, and simulation of the system is adopted in Matlab/Simulink. The simulation result shows that the feedback system with feed-forward block controls the heat value very well, and the simulation result can effectively guide the engineering design of the heat value control system, and the efficiency of engineering is improved.
基金The work was supported by the National Natural Science Foundation of China(No.51808278)the Science Foundation for Youths of Jiangxi Province,China(20192BAB213012)This research was also supported by the College Students’Innovative Entrepreneurial Training Plan Program,China(No.201910403049).
文摘Biomass is a carbon-neutral renewable energy resource.Biochar produced from biomass pyrolysis exhibits preferable characteristics and potential for fossil fuel substitution.For time-and cost-saving,it is vital to establish predictive models to predict biochar properties.However,limited studies focused on the accurate prediction of HHV of biochar by using proximate and ultimate analysis results of various biochar.Therefore,the multi-linear regression(MLR)and the machine learning(ML)models were developed to predict the measured HHV of biochar from the experiment data of this study.In detail,52 types of biochars were produced by pyrolysis from rice straw,pig manure,soybean straw,wood sawdust,sewage sludge,Chlorella Vulgaris,and their mixtures at the temperature ranging from 300 to 800℃.The results showed that the co-pyrolysis of the mixed biomass provided an alternative method to increase the yield of biochar production.The contents of ash,fixed carbon(FC),and C increased as the incremental pyrolysis temperature for most biochars.The Pearson correlation(r)and relative importance analysis between HHV values and the indicators derived from the proximate and ultimate analysis were carried out,and the measured HHV was used to train and test the MLR and the ML models.Besides,ML algorithms,including gradient boosted regression,random forest,and support vector machine,were also employed to develop more widely applicable models for predicting HHV of biochar from an expanded dataset(total 149 data points,including 97 data collected from the published literature).Results showed HHV had strong correlations(|r|>0.9,p<0.05)with ash,FC,and C.The MLR correlations based on either proximate or ultimate analysis showed acceptable prediction performance with test R2>0.90.The ML models showed better performance with test R^(2)around 0.95(random forest)and 0.97–0.98 before and after adding extra data for model construction,respectively.Feature importance analysis of the ML models showed that ash and C were the most important inputs to predict biochar HHV.
文摘In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.
文摘The characteristics of fuel from biomass, coal and some waste materials are lower heat value and different compositions. The lower heat value fuel (LHVF) can be used on power engine such as boiler, gas engine and gas turbine. Some laboratory and pilot work have been done, but the work done on micro-gas turbine is still limited. The characteristics of LHVF can cause the operations change of micro-gas turbine designed for nature gas. Some possible adjustment and modification methods were mentioned for the use of LHVF on micro-gas turbine. One kind of representative LHVF was chosen and the operations of micro-gas turbine were analyzed. The temperature field and the non-uniformity scale of temperature distribution of combustor were calculated using FLUENT. The feasibility of different adjustment and modification methods were analyzed according to the efficiency, output power and the non-uniformity scale of temperature distribution.
基金Provincial Science and Technology Research Project of Guangdong(2014A040401043)
文摘Heat-treated wood has good dimensional stability,corrosion resistance and visual quality,but it is prone to mold,which limits its application.Based on the pH value of heat-treated wood,this study examines the factors affecting the pathogenesis causing heat-treated wood mold.Normally,the pH value of the heat-treated wood is between 4.38 and 5.10,which is suitable for the growth of mold.However,the pH of the heat-treated copper-containing material is between 6.63 and 7.12,which deviates the treated wood from the comfortable growth conditions for the mold,thereby reducing the occurrence of mold.
文摘Based on thermal value theory, the aim of this paper is to deduce the theoretical formulas for evaluating the energy effective utilization degree in technological pyrological processes exemplified by metallurgical heating furnaces. Heat transfer models for continuous heating furnaces, batch-type heating furnaces, and regenerative heating furnaces are established, respectively. By analyzing the movement path of injected infinitesimal heat attached on steel or gas, thermal value equations of continuous, batch-type, and regenerative heating furnaces are derived. Then the influences of such factors as hot charging, gas preheating and intake time of heat on energy effective utilization degree are discussed by thermal value equations. The results show that thermal value rises with hot charging and air preheating for continuous heating furnaces, with shorter intake time when heat is attached on steel or longer intake time when heat is attached on gas for batch-type heating furnaces and that with more heat supply at early heating stage or less at late stage for regenerative heating furnaces.
文摘In recent decades,the generation of Municipal Solid Waste(MSW)is steadily increasing due to urbanization and technological advancement.The col-lection and disposal of municipal solid waste cause considerable environmental degradation,making MSW management a global priority.Waste-to-energy(WTE)using thermochemical process has been identified as the key solution in this area.After evaluating many automated Higher Heating Value(HHV)predic-tion approaches,an Optimal Deep Learning-based HHV Prediction(ODL-HHVP)model for MSW management has been developed.The objective of the ODL-HHVP model is to forecast the HHV of municipal solid waste,based on its oxy-gen,water,hydrogen,carbon,nitrogen,sulphur and ash constituents.In addition,the ODL-HHVP model contains a Deep Support Vector Machine(DSVM)regres-sion component that can accurately predict the HHV.In addition,the Beetle Swarm Optimization(BSO)method is utilised as a hyperparameter optimizer in conjunction with the DSVM model,resulting in the highest HHV prediction accu-racy.A comprehensive simulation study is conducted to validate the performance of the ODL-HHVP method.The Multiple Linear Regression(MLR),Genetic Pro-gramming(GP),Resilient backpropagation(RP),Levenberg Marquardt(LM)and DSVM approaches have attained an ineffective result with RMSEs of 4.360,2.870,3.590,3.100 and 3.050,respectively.The experimentalfindings demon-strate that the ODL-HHVP technique outperforms existing state-of-art technolo-gies in a variety of respects.
基金The research is supported by the National Natural Science Foundation of China(No.11671081)the Fundamental Research Funds for the Central Universities(No.242017K41044).
文摘In this paper,a compact difference scheme is established for the heat equations with multi-point boundary value conditions.The truncation error of the difference scheme is O(τ2+h^4),where t and h are the temporal step size and the spatial step size.A prior estimate of the difference solution in a weighted norm is obtained.The unique solvability,stability and convergence of the difference scheme are proved by the energy method.The theoretical statements for the solution of the difference scheme are supported by numerical examples.
文摘With more ready-to-eat foods and increased shelf-lives, prevention of Listeria monocytogenes contamination has become a necessity for the food industry. This study examined the effects of sublethal heat treatment on the decimal reduction time (D-values) of three L. monocytogenes serotypes (1/2a, 1/2b, 4c), and non-pathogenic L. innocua. The D70 (D-value at 70℃) values of heat-shocked (HS) and non-heat-shocked (NHS) Listeria grown in tryptic soy broth (TSB) were determined. The D70 values of HS L. monocytogenes serotype 1/2a and L. innocua were significantly higher compared to NHS cultures, although by 48 h, the values returned to NHS levels. When HS and NHS 1/2a and 1/2b were inoculated on crab meat and cooked shrimp, the D70 values of HS cultures were at least 2-fold higher, compared to when they were grown in TSB. This increase in heat resistance for the HS cultures may be attributed to the protective effect of the seafood matrix itself.
文摘This work investigated and quantified the calorific values of the main branches and trunks of eleven (11) tropical trees in correlation with their chemical composition in order to assess their suitability for use as credible sources of wood fuel. The determination of the carbon, hydrogen, nitrogen, oxygen and sulphur (CHNOS) content of the samples was done using an organic elemental analyser, while an oxygen bomb calorimeter was used to experimentally determine their corresponding gross heat values. The experimental gross heat values for the branches examined ranged from 18,703.37 kJ/kg in Lophira lanceolata to 21,350.35 kJ/kg in Afzelia africana while that of the trunks ranged from 19,747.74 kJ/kg in Tectonia grandis to 22,408.68 kJ/kg in Prosopis africana. These values were within and about the expected ranges observed for tropical trees and may be considered adequate for wood fuel. The general trend in both branches and trunks was that the higher the carbon content, the higher the gross heat value of sample. The absence of sulphur in almost all the samples except, Prosopis africana, (0.055%) was indicative of the fact that the negative environmental impact with respect to harmful emissions of oxides of sulphur is practically non-existent with respect to these species. In the light of the aforementioned variables, the main branches of Afzelia africana (21,350.35 kJ/kg), Nauclea diderrichii (21,157.30 kJ/kg) and Tectonia grandis (20,257.13 kJ/kg) could be used as credible sources of firewood and charcoal production. With respect to the trunks, the timbers in order of preference would ideally be Prosopis africana (22,408.68 kJ/kg), Nauclea diderichii (21,436.42 kJ/kg) and Brachstigia eurychoma (20,924.7 kJ/kg).
文摘This paper deals with the effect of microwave energy for mullite formation from placer sillimanite. A mullite formation is seen when 60 % SiC and 5% binder are used with the composite charge material, i.e. sillimanite (60%) and Al2O3 (40%). The maximum temperature of the microwave sintering furnace achieved is 1355°C at 2450 W microwave power. Addition of 10 % binder to the same charge material with 60% SiC, the furnace temperature achieved is 1384°C at microwave power 1900 W. Mullite is formed within 25 minutes from the sillimanite, under the above experimental conditions. Whereas under the similar additive conditions, the mullite formed from sillimanite in conventional furnace heating, it took 3 hours at 1300°C. XRD data show the mullite phase for both the products obtained from microwave sintering furnace and conventional furnace. FESEM image analysis shows the mullite formations, SiC fibrous cluster and alumina needles in microwave treated sample. Thus microwave heat source is much more effective for value addition to red sediment placer sillimanite to form mullite in compare to conventional furnace.
文摘In this paper we study inviscid and viscid Burgers equations with initial conditions in the half plane . First we consider the Burgers equations with initial conditions admitting two and three shocks and use the HOPF-COLE transformation to linearize the problems and explicitly solve them. Next we study the Burgers equation and solve the initial value problem for it. We study the asymptotic behavior of solutions and we show that the exact solution of boundary value problem for viscid Burgers equation as viscosity parameter is sufficiently small approach the shock type solution of boundary value problem for inviscid Burgers equation. We discuss both confluence and interacting shocks. In this article a new approach has been developed to find the exact solutions. The results are formulated in classical mathematics and proved with infinitesimal technique of non standard analysis.
基金supported by the Turkish Scientific and Technological Research Council(TUBITAK)(Project No.118Y135).
文摘Higher heating value(HHV)is the key parameter for replacing Refuse-Derived Fuel(RDF)with fossil fuels in the cement industry.HHV can be measured with a bomb calorimeter or predicted from direct elemental data by using regression models.Both methods require the continuous use of special laboratory equipment and are time consuming.To overcome these limitations,this study aims to predict the HHV value of RDF from predicted elemental data by using regression models.Therefore,once the predicted elemental data are generated,there will be no need to have continuous elemental data to predict HHV.Predicted elemental data were generated from direct elemental data and Near Infrared(NIR)camera-based spectrometric data by using a deep learning model.A convolutional neural networks(CNN)model was used for deep learning and was trained with 10,500 NIR image samples,each of which was 28×28×1.Different regression models(Linear,Tree,Support-Vector Machine,Ensemble and Gaussian process)were applied for HHV prediction.According to these results,higher R2 values(>0.85)were obtained with Gaussian process models(except for the Rational Quadratic model)for the predicted elemental data.Among the Gaussian models,the highest R2(0.95)but the lowest Root Mean Square Error(RMSE)(0.0563),Mean Squared Error(MSE)(0.0317)and Mean Absolute Error(MAE)(0.0431)were obtained with the Mattern 5/2 model.The results of predictions from predicted elemental data were compared to predictions from direct elemental data.The results show that the regression from predicted elemental data has an adequate prediction(R2=0.95)compared to the prediction from the direct elemental data(R^(2)=0.99).
