Sunday Alabi - Academia.edu (original) (raw)
Papers by Sunday Alabi
Journal of Materials Science and Chemical Engineering, 2016
Managers of cement plants are gradually becoming aware of the need for soft sensors in product qu... more Managers of cement plants are gradually becoming aware of the need for soft sensors in product quality assessment. Cement clinker quality parameters are mostly measured by offline laboratory analysis or by the use of online analyzers. The measurement delay and cost, associated with these methods, are a concern in the cement industry. In this study, a regression-based model was developed to predict the clinker quality parameters as a function of the raw meal quality and the kiln operating variables. This model has mean squared error, coefficient of determination, worst case relative error and variance account for (in external data) given as 8.96 × 10 −7 , 0.9999, 2.17% and above 97%, respectively. Thus, it is concluded that the developed model can provide real time estimates of the clinker quality parameters and capture wider ranges of real plant operating conditions from first principle-based cement rotary kiln models. Also, the model developed can be utilized online as soft sensor since they contain only variables that are easily measured online.
International Journal of Chemical Engineering and Applications, 2015
Most of the existing models for describing black liquor (BL) viscosity behaviours are applicable ... more Most of the existing models for describing black liquor (BL) viscosity behaviours are applicable over limited ranges of process conditions, whereas BL exhibits varied viscosity behaviours, Newtonian and nonNewtonian, over a wide range of process conditions. These limited-range models, resulting from different bases, may suffer predictions continuity over such wide ranges of conditions. In this paper, attempt was made to jointly model the Newtonian and nonNewtonian viscosity behaviours of literature liquor using artificial neural network (ANN) paradigm. A generalized multilayer feedforward network with 7 hidden neurons and 1 output neuron, having R 2 =1.0 and maximum absolute relative error of ~8% between the actual and predicted data was obtained. Although a model with a higher accuracy is desirable, the proposed single network seems to be a reasonable alternative to the use of the limited-range multiple models for the purposes of describing black liquor viscosity behaviour over a wide range of practical conditions.
Chemical Engineering Transactions, 2019
Diffusers are widely used in technical practice in order to make the transition from a tube/pipe ... more Diffusers are widely used in technical practice in order to make the transition from a tube/pipe or duct of smaller section to a larger one. Low pressure drop across a diffuser is highly required to save pumping or ventilation work. Diffuser pressure drop is caused by enhanced turbulence of the flow, separation of the boundary layer from the diffuser walls and violent vortex formation. As a result, the precise pressure drop coefficient estimation is of high importance. The pressure drop coefficient (?d) of a diffuser depends on diffuser geometry and flow parameters. Traditionally, a number of models must be combined and used with the data obtained from tables (with 2-D interpolation) and charts in a series of steps to obtain ?d. This approach is not suitable for computer-based simulations. Consequently, in this study, a semi-empirical model, for estimating ?d of a conical diffuser, as an explicit function of the flow parameters and the diffuser geometry, is developed. The model was ...
Chemical Engineering Transactions, 2019
Crystallisation occurs in a large group of biotechnological, food, pharmaceutical and chemical pr... more Crystallisation occurs in a large group of biotechnological, food, pharmaceutical and chemical processes. These processes are usually carried out in a batch or fed-batch mode. Traditionally, in sugar industry, the crystals quality is examined at the end of the process. Consequently, lack of real time measurement of sugar crystal size in a fed-batch vacuum evaporative crystalliser hinders the feedback control and optimisation of the crystallisation process. A mathematical model can be used for online estimation of the sugar crystal size. Unfortunately, the existing sugar crystallisation models are not in the form suitable for online implementation. Therefore, based on these existing models and seven process variables namely temperature (T), vacuum pressure (Pvac), feed flowrate (Ff), steam flowrate (Fs), crystallisation time (t), initial super-saturation (S0) and initial crystal size (L0), 128 data sets which were obtained from a 2-level factorial experimental design using MINITAB 14...
Most of the synthetic corrosion inhibitors which are used to protect metals from corrosion are hi... more Most of the synthetic corrosion inhibitors which are used to protect metals from corrosion are highly toxic to both human beings and environment and they are often expensive and non-biodegradable. There is need to produce corrosion inhibitors which are non-toxic to human beings and are environmentally safe, being green inhibitors. Therefore, the use of natural products (reducing agents or antioxidant) extracted from plants as corrosion inhibitors has become a key area of research as they are extremely rich sources of natural chemical compounds that are biodegradable, renewable, and cost-effective as well as can be extracted by simple methods. In this study, the ethanol extract of Cymbopogoncitratus (Poaceae) commonly called Lemongrass was investigated for its phytochemical constituents and antioxidant activity using Diphenylpicrylhydrazyl (DDPH). The result of the phytochemical screening showed the presence of alkaloid, cardiac glycosides, terpenes, carbohydrate, polyphenols, saponi...
International journal of engineering research and technology, 2016
The workability and strength of cement depend on the quality of the clinker produced from the rot... more The workability and strength of cement depend on the quality of the clinker produced from the rotary kiln. The quality of the clinker is dependent on the values of parameters such as the lime saturation factor (LSF), silica moduli (SM), alumina moduli (AM), alite (C3S), etc. This paper critically appraises the current measurement and estimation methods for cement clinker quality parameters. On the one hand, the review shows that the current online hardware sensors can only handle a small sample of clinker per analysis. Moreover, the existing online analyzers (hardware sensors) are expensive to install and lack backup sensors in case they are faulty, down for maintenance or replacement. On the other hand, the review shows that soft (model or software-based) sensors are capable of offering solutions to some of the challenges of the online hardware sensors. However, their predictions depend on the hardware sensors for some input data and the available cement rotary kiln models are not ...
Powder Technology, 2018
In this paper, a comprehensive review of experimental, numerical and artificial intelligence stud... more In this paper, a comprehensive review of experimental, numerical and artificial intelligence studies on the subject of cuttings settling velocity in drilling muds made by researchers over the last seven decades is brought to the fore. In this respect, 91 experimental, 13 numerical simulations and 7 artificial intelligence researches were isolated, reviewed, tabulated and discussed. A comparison of the three methods and the challenges facing each of these methods were also reviewed. The major outcomes of this review include: (1) the unanimity among experimental researchers that mud rheology, particle size and shape and wall effect are major parameters affecting the settling velocity of cuttings in wellbores; (2) the prevalence of cuttings settling velocity experiments done with the mud in static conditions and the wellbore in the vertical configuration; (3) the extensive use of rigid particles of spherical shape to represent drill cuttings due to their usefulness in experimental visualization, particle tracking, and numerical implementation; (4) the existence of an artificial intelligence technique-multi-gene genetic programming (MGGP) which can provide an explicit equation that can help in predicting settling velocity; (5) the limited number of experimental studies factoring in the effect of pipe rotation and well inclination effects on the settling velocity of cuttings and (6) the most applied numerical method for determining settling velocity is the finite element method. Despite these facts, there is need to perform more experiments with real drill cuttings and factor in the effects of conditions such as drillstring rotation and well inclination and use data emanating therefrom to develop
ETP International Journal of Food Engineering, 2016
The super-saturation level of the massecuite is an important quality parameter for sugar crystall... more The super-saturation level of the massecuite is an important quality parameter for sugar crystallisation process, as it determines the seeding point, contributes to the quality of crystals and the cost of production. This paper critically appraises the current measurement and estimation methods for super-saturation level of sugar massecuite. On the one hand, the review shows that the current online hardware sensors lack the necessary accuracy, as the variable to be measured is a multivariable function of many unknowns. Moreover, the sensors require regular maintenance and recalibration to be able to obtain reliable readings. On the other hand, the review shows that soft (model or software-based) sensors are capable of offering solutions to some of the challenges of the online hardware sensors. However, their predictions depend on the hardware sensors for some input data and the available sugar crystallisation models are not in the form suitable for online estimation of super-saturation level of the sugar massecuite. It is concluded that the effective measurement/estimation and control of super-saturation of sugar massecuite is still a challenge in the sugar processing industry. It is therefore recommended that soft sensors should be introduced to complement the online hardware sensors.
ETP International Journal of Food Engineering, 2016
The super-saturation level of the massecuite is an important quality parameter for sugar crystall... more The super-saturation level of the massecuite is an important quality parameter for sugar crystallisation process, as it determines the seeding point, contributes to the quality of crystals and the cost of production. This paper critically appraises the current measurement and estimation methods for super-saturation level of sugar massecuite. On the one hand, the review shows that the current online hardware sensors lack the necessary accuracy, as the variable to be measured is a multivariable function of many unknowns. Moreover, the sensors require regular maintenance and recalibration to be able to obtain reliable readings. On the other hand, the review shows that soft (model or software-based) sensors are capable of offering solutions to some of the challenges of the online hardware sensors. However, their predictions depend on the hardware sensors for some input data and the available sugar crystallisation models are not in the form suitable for online estimation of super-saturation level of the sugar massecuite. It is concluded that the effective measurement/estimation and control of super-saturation of sugar massecuite is still a challenge in the sugar processing industry. It is therefore recommended that soft sensors should be introduced to complement the online hardware sensors.
ETP International Journal of Food Engineering, 2016
The conflicting reports on the performances of the online probes for super-saturation of sugar ma... more The conflicting reports on the performances of the online probes for super-saturation of sugar massecuite necessitate the application of soft-sensor to complement or replace them. Unfortunately, the available sugar crystallisation models which are theoretical and semiempirical in nature are not in the form which can be directly utilised as soft sensor for real time estimation of the massecuite super-saturation. Therefore, in this study, easyto-measure online variables that can be correlated with the super-saturation were identified and used to develop a regression model for online estimation of the supersaturation value of sugar massecuite after seeding. The post-seeding regression model gave coefficient of determination and maximum relative error of 0.994 and 4.7%, respectively. It is therefore concluded that the resulting model has the potential of being used for real time estimation of post-seeding super-saturation of sugar massecuite, as opposed to the existing complex fundamental and semi-empirical sugar crystallisation models.
Journal of Petroleum Science and Engineering, 2018
For an oil well to be said to have been successfully and conclusively drilled, the drilling fluid... more For an oil well to be said to have been successfully and conclusively drilled, the drilling fluid lies at the heart of the solution. Therefore, the guarantee to solving issues in oil well drilling is to contrive an optimal drilling fluid. However, there is usually a complex interplay of factors involved during drilling fluid formulation, property determination, its performance in the well and its relationship with other wellbore drilling parameters. This is so because drilling muds exhibit time dependent properties. This time dependency is the direct product of the synergy among the various active additives that make up the mud and the characteristic of each additive especially at downhole conditions where the effects of temperature and pressure are well pronounced. These additives are more often than not diverse in size, chemical activity, density and surface energy. Deriving knowledge from the data from these parameters in order to develop a functional relationship between them is a challenging task requiring advanced modelling techniques as well as human intuition and experience. The dependence on human intuition and on the experiential knowledge of professional mud engineers lays bare the shortcomings of traditional mud design techniques. Artificial intelligence techniques have been shown to alleviate this challenge. Exploiting the abundant literature on the various applications of artificial intelligence in oil and gas operations, several works that show how and what artificial intelligence techniques are used in the drilling fluid industry, and what have been achieved due to their use have been selected. In this paper, a review of existing artificial intelligence techniques and their applications in drilling fluid engineering is given. This paper also dug up and analyzed the strengths and pitfalls of each artificial intelligence technique. The examination of the strengths and deficiencies was done using the following virtues as the basic criteria: robustness against noise, self-organization, generalization ability, data volume requirements and the convergence speed. The artificial intelligence techniques presented in this paper include: artificial neural networks (ANNs), fuzzy logic, support vector machines (SVM), hybrid intelligent systems (HIS), genetic algorithms (GA), case based reasoning (CBR) and particle swarm algorithm (PSA). An overview of the applications of classical artificial intelligence in drilling fluid engineering is also presented. From the review, it was gathered that the ANN technique is the most widely applied in drilling fluid engineering accounting for over 54% of the papers reviewed; while lost circulation problem was the most predicted well problem related to drilling fluids accounting for over 17% of the mud problems predicted. It was also observed that a blend of AI techniques performed better than when each one of the AI techniques was used singly. Finally, judging the AI techniques on the criteria mentioned above, ANN was found to meet all the listed criteria except for its slow speed of convergence while ANN, GA, SVM and fuzzy logic were all found to be robust against noise.
Journal of Materials Science and Chemical Engineering, 2016
Journal of Chemistry and Chemical Engineering, 2016
Petrochemicals play a vital role in the economy of any nation. The products of the industry are t... more Petrochemicals play a vital role in the economy of any nation. The products of the industry are the building blocks in many industries as they deepen the forward and backward linkages of the petroleum sector with the rest of the economy. The industry uses a variety of hydrocarbon feedstock such as different cuts of naphtha from refinery and natural gas. One of the problems facing the industry is lack of reliable feedstock supplies. Nigeria has the potential to be a major petrochemicals producer. With proven gas reserves currently estimated at 187 tcf, not much has been accomplished with respect to the effective exploitation and utilization of this resource as most of the nation's natural gas production has been flared, liquefied for export or re-injected to enhance greater crude oil recovery. It has become imperative to further find ways to exploit and utilize the nation's natural gas reserves and translate it to the improvement of the nation's economy. Steam reforming of natural gas is one of the avenues for conversion of natural gas to petrochemicals. This paper, however, reviews various ways of utilizing natural gas, examines the process details of steam reforming of natural gas as a route to optimized natural gas utilization and industrialization in Nigeria. Syngas (synthesis gas) is a versatile feedstock for most petrochemicals and chemical intermediates. Thus utilizing natural gas in this way would strengthen the petrochemical industry making it possible for the country to change from raw materials to value-added products supplier, boost the economy and solve the "hydra-headed" problem of unemployment in Nigeria with its multiplier employment effect.
Advances in Chemical Engineering and Science, 2016
The implicit Colebrook equation has been the standard for estimating pipe friction factor in a fu... more The implicit Colebrook equation has been the standard for estimating pipe friction factor in a fully developed turbulent regime. Several alternative explicit models to the Colebrook equation have been proposed. To date, most of the accurate explicit models have been those with three logarithmic functions, but they require more computational time than the Colebrook equation. In this study, a new explicit non-linear regression model which has only two logarithmic functions is developed. The new model, when compared with the existing extremely accurate models, gives rise to the least average and maximum relative errors of 0.0025% and 0.0664%, respectively. Moreover, it requires far less computational time than the Colebrook equation. It is therefore concluded that the new explicit model provides a good trade-off between accuracy and relative computational efficiency for pipe friction factor estimation in the fully developed turbulent flow regime.
Appita Journal: Journal of …, 2012
Informit is an online service offering a wide range of database and full content publication prod... more Informit is an online service offering a wide range of database and full content publication products that deliver the vast majority of Australasian scholarly research to the education, research and business sectors. Informit is the brand that encompasses RMIT Publishing's online products ...
Industrial & Engineering Chemistry Research, 2011
ACSE'05, 2005
Page 1. INTERNAL MODEL CONTROL OF UNCERTAIN SYSTEMS: AN IMPROVED APPROACH. SB Alabi* and O. Taiwo... more Page 1. INTERNAL MODEL CONTROL OF UNCERTAIN SYSTEMS: AN IMPROVED APPROACH. SB Alabi* and O. Taiwo** * Department of Chemical/Petroleum Engineering, Faculty of Engineering, University of Uyo, Uyo, Nigeria. ... Stabil ty margin is defined as cGpwG y = i ...
Asia-Pacific Journal of Chemical Engineering, 2010
ABSTRACT Availability of accurate models for prediction of the viscosity of black liquor (BL) fro... more ABSTRACT Availability of accurate models for prediction of the viscosity of black liquor (BL) from the chemical pulping of pine will facilitate its online monitoring and control and subsequently the optimisation of combustion in a recovery boiler. New Zealand (NZ) BL viscosity data are limited, and no predictive model is available. The viscosities of the NZ BL samples at solids concentrations (SCs) < 50% were obtained at temperature of 25–85 °C and shear rate up to ∼2000 s−1. The samples showed Newtonian behaviour. Existing models from the literature and a binomial model developed in this work were used to fit the viscosity data as a function of SC and temperature. Accuracies of these models were examined for both the log-transformed and the untransformed viscosity data using coefficient of correlation (R) and maximum absolute relative error (MARE) (between the actual and predicted viscosities), respectively, as indices. Although the existing models fit NZ BL viscosity data well when they were log-transformed, they performed poorly when not transformed. Conversely, the new binomial model gave accurate predictions with both the log-transformed and untransformed viscosity data (R = 0.9997; MARE = 5.7%). It is concluded that at low SCs, the viscosity of Newtonian BL can be accurately predicted using the new binomial model. Copyright © 2010 Curtin University of Technology and John Wiley & Sons, Ltd.
Indian Chemical Engineer, 2009
Journal of Materials Science and Chemical Engineering, 2016
Managers of cement plants are gradually becoming aware of the need for soft sensors in product qu... more Managers of cement plants are gradually becoming aware of the need for soft sensors in product quality assessment. Cement clinker quality parameters are mostly measured by offline laboratory analysis or by the use of online analyzers. The measurement delay and cost, associated with these methods, are a concern in the cement industry. In this study, a regression-based model was developed to predict the clinker quality parameters as a function of the raw meal quality and the kiln operating variables. This model has mean squared error, coefficient of determination, worst case relative error and variance account for (in external data) given as 8.96 × 10 −7 , 0.9999, 2.17% and above 97%, respectively. Thus, it is concluded that the developed model can provide real time estimates of the clinker quality parameters and capture wider ranges of real plant operating conditions from first principle-based cement rotary kiln models. Also, the model developed can be utilized online as soft sensor since they contain only variables that are easily measured online.
International Journal of Chemical Engineering and Applications, 2015
Most of the existing models for describing black liquor (BL) viscosity behaviours are applicable ... more Most of the existing models for describing black liquor (BL) viscosity behaviours are applicable over limited ranges of process conditions, whereas BL exhibits varied viscosity behaviours, Newtonian and nonNewtonian, over a wide range of process conditions. These limited-range models, resulting from different bases, may suffer predictions continuity over such wide ranges of conditions. In this paper, attempt was made to jointly model the Newtonian and nonNewtonian viscosity behaviours of literature liquor using artificial neural network (ANN) paradigm. A generalized multilayer feedforward network with 7 hidden neurons and 1 output neuron, having R 2 =1.0 and maximum absolute relative error of ~8% between the actual and predicted data was obtained. Although a model with a higher accuracy is desirable, the proposed single network seems to be a reasonable alternative to the use of the limited-range multiple models for the purposes of describing black liquor viscosity behaviour over a wide range of practical conditions.
Chemical Engineering Transactions, 2019
Diffusers are widely used in technical practice in order to make the transition from a tube/pipe ... more Diffusers are widely used in technical practice in order to make the transition from a tube/pipe or duct of smaller section to a larger one. Low pressure drop across a diffuser is highly required to save pumping or ventilation work. Diffuser pressure drop is caused by enhanced turbulence of the flow, separation of the boundary layer from the diffuser walls and violent vortex formation. As a result, the precise pressure drop coefficient estimation is of high importance. The pressure drop coefficient (?d) of a diffuser depends on diffuser geometry and flow parameters. Traditionally, a number of models must be combined and used with the data obtained from tables (with 2-D interpolation) and charts in a series of steps to obtain ?d. This approach is not suitable for computer-based simulations. Consequently, in this study, a semi-empirical model, for estimating ?d of a conical diffuser, as an explicit function of the flow parameters and the diffuser geometry, is developed. The model was ...
Chemical Engineering Transactions, 2019
Crystallisation occurs in a large group of biotechnological, food, pharmaceutical and chemical pr... more Crystallisation occurs in a large group of biotechnological, food, pharmaceutical and chemical processes. These processes are usually carried out in a batch or fed-batch mode. Traditionally, in sugar industry, the crystals quality is examined at the end of the process. Consequently, lack of real time measurement of sugar crystal size in a fed-batch vacuum evaporative crystalliser hinders the feedback control and optimisation of the crystallisation process. A mathematical model can be used for online estimation of the sugar crystal size. Unfortunately, the existing sugar crystallisation models are not in the form suitable for online implementation. Therefore, based on these existing models and seven process variables namely temperature (T), vacuum pressure (Pvac), feed flowrate (Ff), steam flowrate (Fs), crystallisation time (t), initial super-saturation (S0) and initial crystal size (L0), 128 data sets which were obtained from a 2-level factorial experimental design using MINITAB 14...
Most of the synthetic corrosion inhibitors which are used to protect metals from corrosion are hi... more Most of the synthetic corrosion inhibitors which are used to protect metals from corrosion are highly toxic to both human beings and environment and they are often expensive and non-biodegradable. There is need to produce corrosion inhibitors which are non-toxic to human beings and are environmentally safe, being green inhibitors. Therefore, the use of natural products (reducing agents or antioxidant) extracted from plants as corrosion inhibitors has become a key area of research as they are extremely rich sources of natural chemical compounds that are biodegradable, renewable, and cost-effective as well as can be extracted by simple methods. In this study, the ethanol extract of Cymbopogoncitratus (Poaceae) commonly called Lemongrass was investigated for its phytochemical constituents and antioxidant activity using Diphenylpicrylhydrazyl (DDPH). The result of the phytochemical screening showed the presence of alkaloid, cardiac glycosides, terpenes, carbohydrate, polyphenols, saponi...
International journal of engineering research and technology, 2016
The workability and strength of cement depend on the quality of the clinker produced from the rot... more The workability and strength of cement depend on the quality of the clinker produced from the rotary kiln. The quality of the clinker is dependent on the values of parameters such as the lime saturation factor (LSF), silica moduli (SM), alumina moduli (AM), alite (C3S), etc. This paper critically appraises the current measurement and estimation methods for cement clinker quality parameters. On the one hand, the review shows that the current online hardware sensors can only handle a small sample of clinker per analysis. Moreover, the existing online analyzers (hardware sensors) are expensive to install and lack backup sensors in case they are faulty, down for maintenance or replacement. On the other hand, the review shows that soft (model or software-based) sensors are capable of offering solutions to some of the challenges of the online hardware sensors. However, their predictions depend on the hardware sensors for some input data and the available cement rotary kiln models are not ...
Powder Technology, 2018
In this paper, a comprehensive review of experimental, numerical and artificial intelligence stud... more In this paper, a comprehensive review of experimental, numerical and artificial intelligence studies on the subject of cuttings settling velocity in drilling muds made by researchers over the last seven decades is brought to the fore. In this respect, 91 experimental, 13 numerical simulations and 7 artificial intelligence researches were isolated, reviewed, tabulated and discussed. A comparison of the three methods and the challenges facing each of these methods were also reviewed. The major outcomes of this review include: (1) the unanimity among experimental researchers that mud rheology, particle size and shape and wall effect are major parameters affecting the settling velocity of cuttings in wellbores; (2) the prevalence of cuttings settling velocity experiments done with the mud in static conditions and the wellbore in the vertical configuration; (3) the extensive use of rigid particles of spherical shape to represent drill cuttings due to their usefulness in experimental visualization, particle tracking, and numerical implementation; (4) the existence of an artificial intelligence technique-multi-gene genetic programming (MGGP) which can provide an explicit equation that can help in predicting settling velocity; (5) the limited number of experimental studies factoring in the effect of pipe rotation and well inclination effects on the settling velocity of cuttings and (6) the most applied numerical method for determining settling velocity is the finite element method. Despite these facts, there is need to perform more experiments with real drill cuttings and factor in the effects of conditions such as drillstring rotation and well inclination and use data emanating therefrom to develop
ETP International Journal of Food Engineering, 2016
The super-saturation level of the massecuite is an important quality parameter for sugar crystall... more The super-saturation level of the massecuite is an important quality parameter for sugar crystallisation process, as it determines the seeding point, contributes to the quality of crystals and the cost of production. This paper critically appraises the current measurement and estimation methods for super-saturation level of sugar massecuite. On the one hand, the review shows that the current online hardware sensors lack the necessary accuracy, as the variable to be measured is a multivariable function of many unknowns. Moreover, the sensors require regular maintenance and recalibration to be able to obtain reliable readings. On the other hand, the review shows that soft (model or software-based) sensors are capable of offering solutions to some of the challenges of the online hardware sensors. However, their predictions depend on the hardware sensors for some input data and the available sugar crystallisation models are not in the form suitable for online estimation of super-saturation level of the sugar massecuite. It is concluded that the effective measurement/estimation and control of super-saturation of sugar massecuite is still a challenge in the sugar processing industry. It is therefore recommended that soft sensors should be introduced to complement the online hardware sensors.
ETP International Journal of Food Engineering, 2016
The super-saturation level of the massecuite is an important quality parameter for sugar crystall... more The super-saturation level of the massecuite is an important quality parameter for sugar crystallisation process, as it determines the seeding point, contributes to the quality of crystals and the cost of production. This paper critically appraises the current measurement and estimation methods for super-saturation level of sugar massecuite. On the one hand, the review shows that the current online hardware sensors lack the necessary accuracy, as the variable to be measured is a multivariable function of many unknowns. Moreover, the sensors require regular maintenance and recalibration to be able to obtain reliable readings. On the other hand, the review shows that soft (model or software-based) sensors are capable of offering solutions to some of the challenges of the online hardware sensors. However, their predictions depend on the hardware sensors for some input data and the available sugar crystallisation models are not in the form suitable for online estimation of super-saturation level of the sugar massecuite. It is concluded that the effective measurement/estimation and control of super-saturation of sugar massecuite is still a challenge in the sugar processing industry. It is therefore recommended that soft sensors should be introduced to complement the online hardware sensors.
ETP International Journal of Food Engineering, 2016
The conflicting reports on the performances of the online probes for super-saturation of sugar ma... more The conflicting reports on the performances of the online probes for super-saturation of sugar massecuite necessitate the application of soft-sensor to complement or replace them. Unfortunately, the available sugar crystallisation models which are theoretical and semiempirical in nature are not in the form which can be directly utilised as soft sensor for real time estimation of the massecuite super-saturation. Therefore, in this study, easyto-measure online variables that can be correlated with the super-saturation were identified and used to develop a regression model for online estimation of the supersaturation value of sugar massecuite after seeding. The post-seeding regression model gave coefficient of determination and maximum relative error of 0.994 and 4.7%, respectively. It is therefore concluded that the resulting model has the potential of being used for real time estimation of post-seeding super-saturation of sugar massecuite, as opposed to the existing complex fundamental and semi-empirical sugar crystallisation models.
Journal of Petroleum Science and Engineering, 2018
For an oil well to be said to have been successfully and conclusively drilled, the drilling fluid... more For an oil well to be said to have been successfully and conclusively drilled, the drilling fluid lies at the heart of the solution. Therefore, the guarantee to solving issues in oil well drilling is to contrive an optimal drilling fluid. However, there is usually a complex interplay of factors involved during drilling fluid formulation, property determination, its performance in the well and its relationship with other wellbore drilling parameters. This is so because drilling muds exhibit time dependent properties. This time dependency is the direct product of the synergy among the various active additives that make up the mud and the characteristic of each additive especially at downhole conditions where the effects of temperature and pressure are well pronounced. These additives are more often than not diverse in size, chemical activity, density and surface energy. Deriving knowledge from the data from these parameters in order to develop a functional relationship between them is a challenging task requiring advanced modelling techniques as well as human intuition and experience. The dependence on human intuition and on the experiential knowledge of professional mud engineers lays bare the shortcomings of traditional mud design techniques. Artificial intelligence techniques have been shown to alleviate this challenge. Exploiting the abundant literature on the various applications of artificial intelligence in oil and gas operations, several works that show how and what artificial intelligence techniques are used in the drilling fluid industry, and what have been achieved due to their use have been selected. In this paper, a review of existing artificial intelligence techniques and their applications in drilling fluid engineering is given. This paper also dug up and analyzed the strengths and pitfalls of each artificial intelligence technique. The examination of the strengths and deficiencies was done using the following virtues as the basic criteria: robustness against noise, self-organization, generalization ability, data volume requirements and the convergence speed. The artificial intelligence techniques presented in this paper include: artificial neural networks (ANNs), fuzzy logic, support vector machines (SVM), hybrid intelligent systems (HIS), genetic algorithms (GA), case based reasoning (CBR) and particle swarm algorithm (PSA). An overview of the applications of classical artificial intelligence in drilling fluid engineering is also presented. From the review, it was gathered that the ANN technique is the most widely applied in drilling fluid engineering accounting for over 54% of the papers reviewed; while lost circulation problem was the most predicted well problem related to drilling fluids accounting for over 17% of the mud problems predicted. It was also observed that a blend of AI techniques performed better than when each one of the AI techniques was used singly. Finally, judging the AI techniques on the criteria mentioned above, ANN was found to meet all the listed criteria except for its slow speed of convergence while ANN, GA, SVM and fuzzy logic were all found to be robust against noise.
Journal of Materials Science and Chemical Engineering, 2016
Journal of Chemistry and Chemical Engineering, 2016
Petrochemicals play a vital role in the economy of any nation. The products of the industry are t... more Petrochemicals play a vital role in the economy of any nation. The products of the industry are the building blocks in many industries as they deepen the forward and backward linkages of the petroleum sector with the rest of the economy. The industry uses a variety of hydrocarbon feedstock such as different cuts of naphtha from refinery and natural gas. One of the problems facing the industry is lack of reliable feedstock supplies. Nigeria has the potential to be a major petrochemicals producer. With proven gas reserves currently estimated at 187 tcf, not much has been accomplished with respect to the effective exploitation and utilization of this resource as most of the nation's natural gas production has been flared, liquefied for export or re-injected to enhance greater crude oil recovery. It has become imperative to further find ways to exploit and utilize the nation's natural gas reserves and translate it to the improvement of the nation's economy. Steam reforming of natural gas is one of the avenues for conversion of natural gas to petrochemicals. This paper, however, reviews various ways of utilizing natural gas, examines the process details of steam reforming of natural gas as a route to optimized natural gas utilization and industrialization in Nigeria. Syngas (synthesis gas) is a versatile feedstock for most petrochemicals and chemical intermediates. Thus utilizing natural gas in this way would strengthen the petrochemical industry making it possible for the country to change from raw materials to value-added products supplier, boost the economy and solve the "hydra-headed" problem of unemployment in Nigeria with its multiplier employment effect.
Advances in Chemical Engineering and Science, 2016
The implicit Colebrook equation has been the standard for estimating pipe friction factor in a fu... more The implicit Colebrook equation has been the standard for estimating pipe friction factor in a fully developed turbulent regime. Several alternative explicit models to the Colebrook equation have been proposed. To date, most of the accurate explicit models have been those with three logarithmic functions, but they require more computational time than the Colebrook equation. In this study, a new explicit non-linear regression model which has only two logarithmic functions is developed. The new model, when compared with the existing extremely accurate models, gives rise to the least average and maximum relative errors of 0.0025% and 0.0664%, respectively. Moreover, it requires far less computational time than the Colebrook equation. It is therefore concluded that the new explicit model provides a good trade-off between accuracy and relative computational efficiency for pipe friction factor estimation in the fully developed turbulent flow regime.
Appita Journal: Journal of …, 2012
Informit is an online service offering a wide range of database and full content publication prod... more Informit is an online service offering a wide range of database and full content publication products that deliver the vast majority of Australasian scholarly research to the education, research and business sectors. Informit is the brand that encompasses RMIT Publishing's online products ...
Industrial & Engineering Chemistry Research, 2011
ACSE'05, 2005
Page 1. INTERNAL MODEL CONTROL OF UNCERTAIN SYSTEMS: AN IMPROVED APPROACH. SB Alabi* and O. Taiwo... more Page 1. INTERNAL MODEL CONTROL OF UNCERTAIN SYSTEMS: AN IMPROVED APPROACH. SB Alabi* and O. Taiwo** * Department of Chemical/Petroleum Engineering, Faculty of Engineering, University of Uyo, Uyo, Nigeria. ... Stabil ty margin is defined as cGpwG y = i ...
Asia-Pacific Journal of Chemical Engineering, 2010
ABSTRACT Availability of accurate models for prediction of the viscosity of black liquor (BL) fro... more ABSTRACT Availability of accurate models for prediction of the viscosity of black liquor (BL) from the chemical pulping of pine will facilitate its online monitoring and control and subsequently the optimisation of combustion in a recovery boiler. New Zealand (NZ) BL viscosity data are limited, and no predictive model is available. The viscosities of the NZ BL samples at solids concentrations (SCs) < 50% were obtained at temperature of 25–85 °C and shear rate up to ∼2000 s−1. The samples showed Newtonian behaviour. Existing models from the literature and a binomial model developed in this work were used to fit the viscosity data as a function of SC and temperature. Accuracies of these models were examined for both the log-transformed and the untransformed viscosity data using coefficient of correlation (R) and maximum absolute relative error (MARE) (between the actual and predicted viscosities), respectively, as indices. Although the existing models fit NZ BL viscosity data well when they were log-transformed, they performed poorly when not transformed. Conversely, the new binomial model gave accurate predictions with both the log-transformed and untransformed viscosity data (R = 0.9997; MARE = 5.7%). It is concluded that at low SCs, the viscosity of Newtonian BL can be accurately predicted using the new binomial model. Copyright © 2010 Curtin University of Technology and John Wiley & Sons, Ltd.
Indian Chemical Engineer, 2009