In this work, the performances of a nonlinear dynamic industrial process are examined using grey‐box (GB) models. To understand the dynamics of the system, the transient state is targeted. A white‐box (WB) model holds the prevailing knowledge using some assumptions. The performance of this model is limited. Artificial neural network (ANN) and support vector regression (SVR), which are techniques employed in numerous chemical engineering applications, are employed to construct the associated black‐box (BB) models. GA is used to optimize the SVR parameters. Dimensional and range extrapolations of different manipulated inputs, feed concentrations, feed temperatures, and cooling temperatures of the GB model and BB model are discussed. The different inputs extrapolation has different results because each input's effectiveness in the system is different. The results are compared, and the best model is suggested among the models, ANN, SVR, first principle (FP)‐ANN serial structure, FP‐ANN parallel structure, FP‐SVR serial structure, and FP‐SVR parallel structure.
{"title":"Modelling a chemical plant using grey‐box models employing the support vector regression and artificial neural network","authors":"Mahmood Ghasemi, Hooshang Jazayeri‐Rad, Reza Mosayebi Behbahani","doi":"10.1002/cjce.25416","DOIUrl":"https://doi.org/10.1002/cjce.25416","url":null,"abstract":"In this work, the performances of a nonlinear dynamic industrial process are examined using grey‐box (GB) models. To understand the dynamics of the system, the transient state is targeted. A white‐box (WB) model holds the prevailing knowledge using some assumptions. The performance of this model is limited. Artificial neural network (ANN) and support vector regression (SVR), which are techniques employed in numerous chemical engineering applications, are employed to construct the associated black‐box (BB) models. GA is used to optimize the SVR parameters. Dimensional and range extrapolations of different manipulated inputs, feed concentrations, feed temperatures, and cooling temperatures of the GB model and BB model are discussed. The different inputs extrapolation has different results because each input's effectiveness in the system is different. The results are compared, and the best model is suggested among the models, ANN, SVR, first principle (FP)‐ANN serial structure, FP‐ANN parallel structure, FP‐SVR serial structure, and FP‐SVR parallel structure.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141777194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The effect of organic and inorganic compounds, commonly present in the mineralogy of crude oil and/or added in the washing processes of extracted crude, on the removal efficiency of emulsified oils present in waste washing waters was investigated by means of flocculation. Approximately 90% of the emulsified oil could be removed using an anionic flocculant, providing a residual turbidity below 100 NTU. The yield depended on the nature of the organic and inorganic components present. The higher the chain length of the main organic component, the greater the flocculant concentration required to remove the oil. Several components had an effect of emulsification (e.g., octane, decane), some of which rendered de‐oiling process completely ineffective (e.g., naphthenic acids). Aliphatics were the most difficult to eliminate, requiring flocculant levels in the 200–300 ppm range. This is in contrast to 75–100 ppm levels which were required to remove bi‐ and poly‐cyclic aromatics. Heavy oils were more difficult to remove than light oils. There was a strong effect of the pH of the aqueous phase. The optimum was pH = 2.0. Virtually all inorganic compounds reduced the efficiency of removing oil from water when spiked at 1%. The only exception was sodium carbonate which acted as a de‐emulsifier. Monovalent salts have a minor effect on de‐oiling, with efficiencies remaining at 80%. Divalent chlorides reduced the de‐oiling efficiency to 70% while sulphates had a more severe influence. The de‐oiling efficiency was lowered substantially with the addition of clays, zinc, cadmium, ferric oxide, calcium carbonate, and dibenyhlthiophene.
{"title":"Crude oil removal from water: Influence of organic phase composition and mineral content","authors":"Ignacio Rintoul, Thomas Uldry, David Hunkeler","doi":"10.1002/cjce.25412","DOIUrl":"https://doi.org/10.1002/cjce.25412","url":null,"abstract":"The effect of organic and inorganic compounds, commonly present in the mineralogy of crude oil and/or added in the washing processes of extracted crude, on the removal efficiency of emulsified oils present in waste washing waters was investigated by means of flocculation. Approximately 90% of the emulsified oil could be removed using an anionic flocculant, providing a residual turbidity below 100 NTU. The yield depended on the nature of the organic and inorganic components present. The higher the chain length of the main organic component, the greater the flocculant concentration required to remove the oil. Several components had an effect of emulsification (e.g., octane, decane), some of which rendered de‐oiling process completely ineffective (e.g., naphthenic acids). Aliphatics were the most difficult to eliminate, requiring flocculant levels in the 200–300 ppm range. This is in contrast to 75–100 ppm levels which were required to remove bi‐ and poly‐cyclic aromatics. Heavy oils were more difficult to remove than light oils. There was a strong effect of the pH of the aqueous phase. The optimum was pH = 2.0. Virtually all inorganic compounds reduced the efficiency of removing oil from water when spiked at 1%. The only exception was sodium carbonate which acted as a de‐emulsifier. Monovalent salts have a minor effect on de‐oiling, with efficiencies remaining at 80%. Divalent chlorides reduced the de‐oiling efficiency to 70% while sulphates had a more severe influence. The de‐oiling efficiency was lowered substantially with the addition of clays, zinc, cadmium, ferric oxide, calcium carbonate, and dibenyhlthiophene.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141777268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Superimposition of oscillatory flow over the axial flow is expected to further enhance the mixing phenomenon based on the limited reported literature. A detailed study on the physics of such superimposed flows will be useful to widen the scope of application of static mixers with superimposed oscillatory flow in continuous modes of operation for several purposes. The flow behaviour of a water–vinyl acetate system in a milli‐channel with static internals is studied under the laminar flow regime using computational fluid dynamics (CFD) as a tool. A CFD model is developed and validated with reported literature on a Kenics static mixer. The effect of oscillatory flow superimposed over the axial flow in a milli‐channel is studied for Ren = 5 and Reo = 20–65. Residence time distribution (RTD) studies have been carried out and compared numerically for two different geometries, (1) tube without an internal and (2) tube with internals, for two different velocities, (1) net axial velocity and (2) superimposed oscillatory velocity. Results of these RTD studies indicate a sharp distribution in the channel with static internals having superimposed oscillatory flow followed by the channel with static internals with net axial velocity and then a tube without an internal. It is also found that Péclet number (Pe) for static internals with oscillatory flow > net axial flow > tube without an internal (736 > 641 > 315). Further, velocity magnitude, pressure, and Q‐criterion are discussed in detail to understand fluid flow behaviour in the milli‐channel. From this research, it is understood that superimposing oscillatory flow along with static internals resulted in enhanced mixing when compared with a tube with no internal.
{"title":"Effect of superimposing oscillatory flow in a milli‐channel with static internals—A numerical study","authors":"Navya Manthani, Vijaya Lakshmi Nanavath, Sreepriya Vedantam","doi":"10.1002/cjce.25415","DOIUrl":"https://doi.org/10.1002/cjce.25415","url":null,"abstract":"Superimposition of oscillatory flow over the axial flow is expected to further enhance the mixing phenomenon based on the limited reported literature. A detailed study on the physics of such superimposed flows will be useful to widen the scope of application of static mixers with superimposed oscillatory flow in continuous modes of operation for several purposes. The flow behaviour of a water–vinyl acetate system in a milli‐channel with static internals is studied under the laminar flow regime using computational fluid dynamics (CFD) as a tool. A CFD model is developed and validated with reported literature on a Kenics static mixer. The effect of oscillatory flow superimposed over the axial flow in a milli‐channel is studied for Re<jats:sub>n</jats:sub> = 5 and Re<jats:sub>o</jats:sub> = 20–65. Residence time distribution (RTD) studies have been carried out and compared numerically for two different geometries, (1) tube without an internal and (2) tube with internals, for two different velocities, (1) net axial velocity and (2) superimposed oscillatory velocity. Results of these RTD studies indicate a sharp distribution in the channel with static internals having superimposed oscillatory flow followed by the channel with static internals with net axial velocity and then a tube without an internal. It is also found that Péclet number (Pe) for static internals with oscillatory flow > net axial flow > tube without an internal (736 > 641 > 315). Further, velocity magnitude, pressure, and Q‐criterion are discussed in detail to understand fluid flow behaviour in the milli‐channel. From this research, it is understood that superimposing oscillatory flow along with static internals resulted in enhanced mixing when compared with a tube with no internal.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141777195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fluidized bed technology has a 100‐year history of delivering energy solutions to the world. Examples include fluid catalytic cracking, coal combustion and gasification, and fluid coking. Moving forward, fluidization technology has the potential to underpin the development of entirely new sustainable processes in the energy transition and the circular economy and many of these will be advanced by small‐and‐medium enterprises (SMEs) and start‐ups. Focused, low‐cost, and time‐bound research outcomes will be needed to support these SMEs as they bring their new technologies to market as quickly as possible. This paper first summarizes some of the fluidized bed technologies that will play a key role in the energy transition and then considers how the strategic concept of discovery driven growth can lead to focused, rapid, and low‐cost information. The experimental data can then be used to develop hybrid models using machine learning methods that will be more robust, accurate, and reliable models. With focused, interdisciplinary research, fluidization models may be developed that would allow fluidized beds to go directly from lab or pilot scale directly to commercial. This would reduce development costs and timelines dramatically, hence bringing these new technologies to market more quickly. Early commercialization will allow the environmental benefits to begin to accrue earlier and will improve returns on investment.
{"title":"Fluidized bed applications and modern scale‐up tools for the energy transition","authors":"Todd Pugsley","doi":"10.1002/cjce.25420","DOIUrl":"https://doi.org/10.1002/cjce.25420","url":null,"abstract":"Fluidized bed technology has a 100‐year history of delivering energy solutions to the world. Examples include fluid catalytic cracking, coal combustion and gasification, and fluid coking. Moving forward, fluidization technology has the potential to underpin the development of entirely new sustainable processes in the energy transition and the circular economy and many of these will be advanced by small‐and‐medium enterprises (SMEs) and start‐ups. Focused, low‐cost, and time‐bound research outcomes will be needed to support these SMEs as they bring their new technologies to market as quickly as possible. This paper first summarizes some of the fluidized bed technologies that will play a key role in the energy transition and then considers how the strategic concept of discovery driven growth can lead to focused, rapid, and low‐cost information. The experimental data can then be used to develop hybrid models using machine learning methods that will be more robust, accurate, and reliable models. With focused, interdisciplinary research, fluidization models may be developed that would allow fluidized beds to go directly from lab or pilot scale directly to commercial. This would reduce development costs and timelines dramatically, hence bringing these new technologies to market more quickly. Early commercialization will allow the environmental benefits to begin to accrue earlier and will improve returns on investment.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"74 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141643219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Aguilar‐López, Iraiz González‐Viveros, P. López‐Pérez
The main goal of this proposal is to present a class of nonlinear controllers for regulation and set point changes in continuous chemical reactors. The proposed control law has in its mathematical structure a proportional term of the regulation error to provide closed‐loop stability and a sinusoidal term, which can compensate for the nonlinearities of the plant. The closed‐loop stability of the plant is demonstrated via Lyapunov analysis, which reveals an asymptotic convergence of the control output to the required set points. Furthermore, the analysis of the regulation error's dynamic under the considered assumptions leads us to conclude that exponential stability is also reached. The controller is implemented via numerical experiments in two examples to generalize the applicability of the proposed approach by considering continuous stirred‐tank reactors models. The first case considers autocatalytic chemical oscillatory reactions that induce chaotic behaviour. For the second case, a process of acetone, butanol, and ethanol (ABE) fermentation through Clostridium acetobutylicum is considered. The proposed strategy shows an adequate performance because it can reach the required set point without long time settings and overshoot. A comparison with a smooth sliding‐mode and a standard proportional‐integral (PI) controller indicates the advantages of the proposed control approach.
{"title":"Sinusoidal control strategy applied to continuous stirred‐tank reactors: Asymptotic and exponential convergence","authors":"R. Aguilar‐López, Iraiz González‐Viveros, P. López‐Pérez","doi":"10.1002/cjce.25411","DOIUrl":"https://doi.org/10.1002/cjce.25411","url":null,"abstract":"The main goal of this proposal is to present a class of nonlinear controllers for regulation and set point changes in continuous chemical reactors. The proposed control law has in its mathematical structure a proportional term of the regulation error to provide closed‐loop stability and a sinusoidal term, which can compensate for the nonlinearities of the plant. The closed‐loop stability of the plant is demonstrated via Lyapunov analysis, which reveals an asymptotic convergence of the control output to the required set points. Furthermore, the analysis of the regulation error's dynamic under the considered assumptions leads us to conclude that exponential stability is also reached. The controller is implemented via numerical experiments in two examples to generalize the applicability of the proposed approach by considering continuous stirred‐tank reactors models. The first case considers autocatalytic chemical oscillatory reactions that induce chaotic behaviour. For the second case, a process of acetone, butanol, and ethanol (ABE) fermentation through Clostridium acetobutylicum is considered. The proposed strategy shows an adequate performance because it can reach the required set point without long time settings and overshoot. A comparison with a smooth sliding‐mode and a standard proportional‐integral (PI) controller indicates the advantages of the proposed control approach.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"15 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sodium polyacrylate (PAAS), a macromolecule surfactant, was employed in the synthesis of polyvinyl butyral (PVB) using a deep eutectic solvent (DES) as the catalyst. Contrasting with traditional low molecular weight surfactants, scanning electron microscopy (SEM) analysis has confirmed that PAAS enhanced the uniformity of PVB granules while minimizing PAAS residuals, facilitating the production of films with superior transparency and resistance to yellowing. Investigations into the effects of varying molecular weights, dosages of PAAS, and aging times on the properties of PVB revealed that an increase in PAAS molecular weight correspondingly raised the acetal degree (AD) of PVB without affecting the molecular weight of PVB itself. Furthermore, yhe dosage of PAAS significantly impacted the properties of PVB, whereas aging time exhibits minimal influence on the AD of PVB. 1H‐NMR analysis indicated that the structural stability of PVB is due to the dominance of meso acetal isomers, which improved its mechanical properties when synthesized with PAAS3 (molecular weight 60,000 g/mol), containing 91.5% hexamethylene cycloacetal. Notably, compared to PVB synthesized using sodium dodecyl sulphate (SDS), PVB synthesized with PAAS3 exhibits superior mechanical properties, with significantly improved tensile strength and elongation. This phenomenon is further elucidated by SEM images. A comparison between the optimized self‐made PVB and commercial PVB shows that the self‐made PVB performs better, highlighting the critical role of macromolecular PAAS in enhancing the structure and mechanical properties of PVB.
{"title":"Effect of macromolecular sodium polyacrylate on the molecular structure and properties of polyvinyl butyral synthesized deep eutectic solvent","authors":"Xiaolu Lv, Yumeng Zhang, Fengtao Li, Xuelian He","doi":"10.1002/cjce.25391","DOIUrl":"https://doi.org/10.1002/cjce.25391","url":null,"abstract":"Sodium polyacrylate (PAAS), a macromolecule surfactant, was employed in the synthesis of polyvinyl butyral (PVB) using a deep eutectic solvent (DES) as the catalyst. Contrasting with traditional low molecular weight surfactants, scanning electron microscopy (SEM) analysis has confirmed that PAAS enhanced the uniformity of PVB granules while minimizing PAAS residuals, facilitating the production of films with superior transparency and resistance to yellowing. Investigations into the effects of varying molecular weights, dosages of PAAS, and aging times on the properties of PVB revealed that an increase in PAAS molecular weight correspondingly raised the acetal degree (AD) of PVB without affecting the molecular weight of PVB itself. Furthermore, yhe dosage of PAAS significantly impacted the properties of PVB, whereas aging time exhibits minimal influence on the AD of PVB. 1H‐NMR analysis indicated that the structural stability of PVB is due to the dominance of meso acetal isomers, which improved its mechanical properties when synthesized with PAAS3 (molecular weight 60,000 g/mol), containing 91.5% hexamethylene cycloacetal. Notably, compared to PVB synthesized using sodium dodecyl sulphate (SDS), PVB synthesized with PAAS3 exhibits superior mechanical properties, with significantly improved tensile strength and elongation. This phenomenon is further elucidated by SEM images. A comparison between the optimized self‐made PVB and commercial PVB shows that the self‐made PVB performs better, highlighting the critical role of macromolecular PAAS in enhancing the structure and mechanical properties of PVB.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"2 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ultrasound‐assisted dehydration of fructose into 5‐hydroxymethylfurfural (5‐HMF) and subsequent oxidation to furandicarboxylic acid (2, 5‐FDCA) is studied in the current work with the main objective being to elucidate the effectiveness of ultrasound for intensified synthesis. The effect of reaction parameters like ultrasound power, duty cycle, reaction time, reaction temperature, solid to solvent ratio, and fructose concentration on the dehydration of fructose into 5‐HMF has been studied. Optimized conditions established were ultrasonic power of 140 W, duty cycle of 60%, reaction time of 60 min, temperature of 100°C, and fructose:dimethylsulfoxide (DMSO) ratio of 3:100 (g/mL), which resulted in the highest 5‐HMF yield of 96% and fructose conversion of 100%. The conventional method carried out at optimized conditions resulted in only 13.5% as 5‐HMF yield. The obtained 5‐HMF was further oxidized to FDCA using Pd/C as the catalyst, H2O/DMSO as solvent, and K2CO3 as a base also using ultrasonic irradiation at 140 W power and 22 kHz frequency in the presence and absence of O2 as oxidant. 100% conversion of 5‐ HMF was obtained in 30 min and 4 h using ultrasound in the presence of O2 and in absence of O2, respectively. 75% conversion of 5‐HMF was observed using the conventional method in 5 h in the presence of O2. Overall, the intensification benefits of using ultrasound at both steps of synthesis has been successfully elucidated.
{"title":"Intensification of fructose dehydration into 5‐HMF and subsequent oxidation to 2,5‐FDCA using ultrasound","authors":"Danwyn J. Aranha, Madhuri M. Kininge, P. Gogate","doi":"10.1002/cjce.25409","DOIUrl":"https://doi.org/10.1002/cjce.25409","url":null,"abstract":"Ultrasound‐assisted dehydration of fructose into 5‐hydroxymethylfurfural (5‐HMF) and subsequent oxidation to furandicarboxylic acid (2, 5‐FDCA) is studied in the current work with the main objective being to elucidate the effectiveness of ultrasound for intensified synthesis. The effect of reaction parameters like ultrasound power, duty cycle, reaction time, reaction temperature, solid to solvent ratio, and fructose concentration on the dehydration of fructose into 5‐HMF has been studied. Optimized conditions established were ultrasonic power of 140 W, duty cycle of 60%, reaction time of 60 min, temperature of 100°C, and fructose:dimethylsulfoxide (DMSO) ratio of 3:100 (g/mL), which resulted in the highest 5‐HMF yield of 96% and fructose conversion of 100%. The conventional method carried out at optimized conditions resulted in only 13.5% as 5‐HMF yield. The obtained 5‐HMF was further oxidized to FDCA using Pd/C as the catalyst, H2O/DMSO as solvent, and K2CO3 as a base also using ultrasonic irradiation at 140 W power and 22 kHz frequency in the presence and absence of O2 as oxidant. 100% conversion of 5‐ HMF was obtained in 30 min and 4 h using ultrasound in the presence of O2 and in absence of O2, respectively. 75% conversion of 5‐HMF was observed using the conventional method in 5 h in the presence of O2. Overall, the intensification benefits of using ultrasound at both steps of synthesis has been successfully elucidated.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"29 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modellers of chemical processes with knowledge about plausible parameter values use Bayesian parameter estimation methods to account for their prior beliefs. Some modellers specify prior distributions with finite parameter ranges, such as uniform distributions and truncated normal distributions, because they better account for knowledge about realistic parameter ranges than normal prior distributions with parameter values ranging between and . We derive closed‐form objective functions for Bayesian parameter estimation with truncated normal priors and uniform priors, for the first time, so that parameter estimation can be performed by solving simple optimization problems rather than using complex sampling‐based techniques. A parametric bootstrapping method that considers truncated normal priors and model nonlinearity is proposed to determine 95% confidence intervals and joint confidence regions. A pharmaceutical case study is used to show the effectiveness of the proposed objective functions and bootstrapping methodology. Confidence regions from bootstrapping are similar to linearization‐based confidence regions that do not account for truncation when truncated areas in normal prior distributions are relatively small. More truncation, which corresponds to more‐precise prior knowledge about the parameters, results in smaller joint confidence regions. The proposed methods will be attractive for parameter estimation in complex process models because they can be less computationally intensive than Markov chain Monte Carlo methods that provide similar results.
{"title":"Bayesian parameter estimation using truncated normal distributions as priors for parameters in fundamental models of chemical processes","authors":"Lauren A. Gibson, Kimberley B. McAuley","doi":"10.1002/cjce.25398","DOIUrl":"https://doi.org/10.1002/cjce.25398","url":null,"abstract":"Modellers of chemical processes with knowledge about plausible parameter values use Bayesian parameter estimation methods to account for their prior beliefs. Some modellers specify prior distributions with finite parameter ranges, such as uniform distributions and truncated normal distributions, because they better account for knowledge about realistic parameter ranges than normal prior distributions with parameter values ranging between and . We derive closed‐form objective functions for Bayesian parameter estimation with truncated normal priors and uniform priors, for the first time, so that parameter estimation can be performed by solving simple optimization problems rather than using complex sampling‐based techniques. A parametric bootstrapping method that considers truncated normal priors and model nonlinearity is proposed to determine 95% confidence intervals and joint confidence regions. A pharmaceutical case study is used to show the effectiveness of the proposed objective functions and bootstrapping methodology. Confidence regions from bootstrapping are similar to linearization‐based confidence regions that do not account for truncation when truncated areas in normal prior distributions are relatively small. More truncation, which corresponds to more‐precise prior knowledge about the parameters, results in smaller joint confidence regions. The proposed methods will be attractive for parameter estimation in complex process models because they can be less computationally intensive than Markov chain Monte Carlo methods that provide similar results.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"116 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lin Zou, Wan Shang, Tingting Min, Biyu Zhang, Lu Yuan, Xin Peng, Xiangping Chen
This study aimed to develop iminodiethylamine oxime graphite oxide (IOGO) through the grafting of iminodiethylamine oxime onto graphene oxide (GO) via amidation and oximation. The primary objective was to investigate the adsorption characteristics of Pb(II) and Cd(II) ions on IOGO. Results demonstrated that IOGO exhibited exceptional adsorption capabilities, reaching maximum adsorption capacities of 798.87 mg/g for Pb(II) and 283.50 mg/g for Cd(II). Remarkably, IOGO maintained its high adsorption performance over five consecutive adsorption cycles. Specifically, the adsorption capacity for Pb(II) remained significantly stable at 480.78 mg/g, exhibiting only an 8.77% decrease. Similarly, the Cd(II) adsorption capacity remained robust at 204.13 mg/g, demonstrating a modest reduction of 10.47%. These findings underscore the feasibility of employing IOGO in repeated adsorption processes, thereby showcasing its potential for practical applications in the removal of heavy metals from aqueous solutions.
{"title":"Efficient removal of Pb(II) and Cd(II) ions from wastewater using amidoxime functionalized graphene oxide","authors":"Lin Zou, Wan Shang, Tingting Min, Biyu Zhang, Lu Yuan, Xin Peng, Xiangping Chen","doi":"10.1002/cjce.25413","DOIUrl":"https://doi.org/10.1002/cjce.25413","url":null,"abstract":"This study aimed to develop iminodiethylamine oxime graphite oxide (IOGO) through the grafting of iminodiethylamine oxime onto graphene oxide (GO) via amidation and oximation. The primary objective was to investigate the adsorption characteristics of Pb(II) and Cd(II) ions on IOGO. Results demonstrated that IOGO exhibited exceptional adsorption capabilities, reaching maximum adsorption capacities of 798.87 mg/g for Pb(II) and 283.50 mg/g for Cd(II). Remarkably, IOGO maintained its high adsorption performance over five consecutive adsorption cycles. Specifically, the adsorption capacity for Pb(II) remained significantly stable at 480.78 mg/g, exhibiting only an 8.77% decrease. Similarly, the Cd(II) adsorption capacity remained robust at 204.13 mg/g, demonstrating a modest reduction of 10.47%. These findings underscore the feasibility of employing IOGO in repeated adsorption processes, thereby showcasing its potential for practical applications in the removal of heavy metals from aqueous solutions.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141611832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paulo A. L. de Souza, Raja Muhammad Afzal, Felipe Gomes Camacho, Nader Mahinpey
Tri‐reforming of methane (TRM) is a promising technology for the simultaneous production of hydrogen and syngas with high energy efficiency (above 70%). However, catalyst design for TRM is challenging due to complex reaction kinetics and the need for catalyst materials with great stability and activity. Machine learning, particularly artificial neural networks (ANNs), has emerged as a powerful tool in catalyst development for the TRM process. More than 6000 data points were selected to build individual models for each reaction and later coupled into an ensembled model used to make predictions considering TRM experimental conditions. The reaction temperature input parameter was found to be the one with major relative importance (61.4%), contributing the most to changes in the CH4 conversion %. Dry reforming of methane (DRM), steam reforming of methane (SRM), and partial oxidation of methane (POX) models observed errors (RMSE) of 3.44%, 2.20%, 1.61%, respectively, with the ensembled model having a maximum error of 4.48%. The newly devised artificial neural network (ANN) model demonstrates remarkable capability in accurately predicting CH4 conversion for novel catalyst formulations in the TRM process, exhibiting minimal error deviation.
{"title":"Catalyst development for the tri‐reforming of methane (TRM) process by integrated singular machine learning models","authors":"Paulo A. L. de Souza, Raja Muhammad Afzal, Felipe Gomes Camacho, Nader Mahinpey","doi":"10.1002/cjce.25397","DOIUrl":"https://doi.org/10.1002/cjce.25397","url":null,"abstract":"Tri‐reforming of methane (TRM) is a promising technology for the simultaneous production of hydrogen and syngas with high energy efficiency (above 70%). However, catalyst design for TRM is challenging due to complex reaction kinetics and the need for catalyst materials with great stability and activity. Machine learning, particularly artificial neural networks (ANNs), has emerged as a powerful tool in catalyst development for the TRM process. More than 6000 data points were selected to build individual models for each reaction and later coupled into an ensembled model used to make predictions considering TRM experimental conditions. The reaction temperature input parameter was found to be the one with major relative importance (61.4%), contributing the most to changes in the CH<jats:sub>4</jats:sub> conversion %. Dry reforming of methane (DRM), steam reforming of methane (SRM), and partial oxidation of methane (POX) models observed errors (RMSE) of 3.44%, 2.20%, 1.61%, respectively, with the ensembled model having a maximum error of 4.48%. The newly devised artificial neural network (ANN) model demonstrates remarkable capability in accurately predicting CH<jats:sub>4</jats:sub> conversion for novel catalyst formulations in the TRM process, exhibiting minimal error deviation.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"244 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141611834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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