Proceedings of the Canadian Engineering Education Association, 2015
An “expert-follower” approach toconduct laboratory courses is outlined in this article. Themain o... more An “expert-follower” approach toconduct laboratory courses is outlined in this article. Themain objective of the proposed procedure is to enhancegraduate attributes. Two important attributes namely,investigation and team work are focused. In this setting,one team becomes the designated expert team for anexperiment. Based on the range of operating conditions ofequipment, the expert team will decide different sets ofexperimental conditions. The expert team will first run theexperiment and the follower teams will run in thefollowing weeks, each at a different set of conditions. Thefollower teams will be briefed by the expert team prior toand during the experiment. The expert team will gatherdata from the follower teams every week. Each team willbe designated expert for one experiment while followerfor the others. The expert team will have a large set ofdata to investigate the characteristics of thecorresponding equipment. They will have to analyze data,identify any abnormality and prob...
Lifelong learning might be one of the most important attributes for students pursuing a professio... more Lifelong learning might be one of the most important attributes for students pursuing a professional degree, e.g. medicine, law or engineering. From teaching and assessment point of view, it may be one of the most challenging attributes. In engineering programs, it is one of the required graduate attributes identified by the Canadian Engineering Accreditation Board (CEAB), the Accreditation Board for Engineering and Technology (ABET) in the USA and other accreditation bodies around the world. In this article we present a laboratory procedure to teach and assess lifelong learning in an engineering program. The concept of lifelong learning as defined by different accreditation bodies is discussed first and corresponding learning outcomes are developed using the revised Bloom's taxonomy. Student activities required to achieve the outcomes are then devised. The links between pre-, in-and post-lab activities and the learning outcomes are established and the approach to run a laborato...
This paper presents a new integrated methodology for fault detection and diagnosis. The methodolo... more This paper presents a new integrated methodology for fault detection and diagnosis. The methodology is built using the multivariate exponentially weighted moving average principal component analysis (MEWMA-PCA) and the Bayesian network (BN) model. The fault detection is carried out using the MEWMA-PCA; diagnosis is completed utilizing the BN models. A novel supervisory learning-based methodology has been proposed to develop the BNs from the historical fault symptoms. Although the algorithm has been extensively applied to the Tennessee Eastman (TE) chemical process, monitoring of three specific (difficult to observe) faults, IDV 3, IDV 9, and IDV 15, has been demonstrated in this article. Most of the existing data-based methods have faced the challenge to detect these faults with a good detection rate (DR). Hence, these faults have been reported as either unobservable or strenuous to detect. Overall, fault detection performance of the squared prediction error (SPE) statistics combined with the MEWMA-PCA wa...
An output error optimization approach for identification of parsimonious fractional order models ... more An output error optimization approach for identification of parsimonious fractional order models using multi-frequency sinusoids as input is proposed. The algorithm simultaneously estimates orders, parameters and the delay of simple models with fractional orders using the Gauss-Newton optimization approach. Optimization-based methods for fractional order model identification require evaluation of the sensitivity functions which include the logarithmic derivatives of the input signal. In the existing literature, central difference or similar methods are used to numerically calculate the Jacobian matrix due to difficulties with numerical simulation of the logarithmic derivatives. We assume deterministic input signals and provide analytical expressions for the logarithmic derivatives of single and multiple frequency sinusoids. Relevant mathematical derivations are presented and the analytical expressions are used to evaluate the Jacobian. Effects of noise to signal ratio, input frequen...
International Journal of Pressure Vessels and Piping
Abstract This paper presents a predictive probabilistic model to estimate the overall economic im... more Abstract This paper presents a predictive probabilistic model to estimate the overall economic impacts of pitting corrosion by considering both the corrosion costs and significant losses that may occur if failures occur because of pitting corrosion. The major loss categories are considered as business loss and accidental loss. Models are proposed to estimate the elements in each loss category. Corrosion prevention, monitoring, maintenance and management (CPM3) costs are considered as the main categories of corrosion costs and the probabilistic models are proposed to estimate these costs. The Monte Carlo (MC) method is used to integrate the loss and cost models and also to address the uncertainties in these models. The effect of inflation on loss values and the mitigating impact of CPM3 costs are also taken into consideration in the developed models. The application of the proposed risk model is demonstrated using a piping case study. As highlighted in the case study, the developed models help to assess corrosion economic risk, which is used for corrosion prevention and control's decision-making.
The Canadian Journal of Chemical Engineering, 2016
An overview of identification of continuous-time models from step responses using the integral eq... more An overview of identification of continuous-time models from step responses using the integral equation approach is presented. Both open loop and closed loop identification as well as identification of multiple-input-multiple-output (MIMO) models are considered. Solutions to practical implementation problems are provided and methods for identification with transient initial conditions using raw data as well as estimation algorithms in the presence of disturbances are outlined. The methodologies are presented in a simplified way using the example of a first order model; however, the algorithms are applicable for models with higher orders. Solution techniques for the estimation equations are also discussed. Identification results under different experimental conditions and data quality are presented to demonstrate the performance of the algorithms. A number of experimental and simulation examples are presented to demonstrate the applicability of the approach. This article is protected by copyright. All rights reserved
Alarm flooding is a significant problem in the process industries. To solve this problem, a scena... more Alarm flooding is a significant problem in the process industries. To solve this problem, a scenario-based early warning system design methodology is proposed. It comprises three steps: (i) scenario identification: events are identified by HAZOP analysis, variables are allocated to the scenario-based group, and the variables states correlated to the scenarios are identified; (ii) model development: Bayesian network of all variables is learned from the process data, and the events nodes are appended according to expert knowledge to construct the Bayesian network model of a scenario-based early warning system; (iii) model implementation: the model is applied online to monitor process, the monitored variables continuously produce evidence, update the events probabilities, find the root causes, and give an events warning message together with the root cause to operators. The methodology implementation and salient points are explained with the help of an easy to follow simple case study.
Process safety and risk assessment are often multidimensional and hence require the joint modelin... more Process safety and risk assessment are often multidimensional and hence require the joint modeling of several potentially correlated random variables. Any effort to address the correlation among the input variables is important and could improve the accuracy in practical applications of risk assessment models. This paper discusses the problems with correlated variables used in risk assessment and presents a copula-based technique to model dependency among variables to improve uncertainty analysis. Using the copula approach, capturing the dependence structure among different risk factors and estimating the univariate risk marginals can be separated. This advantage simplifies the overall risk estimation for systems with multiple dependent risk sources. The advantage of the copula-based framework for generalization over the traditional correlation analysis technique is demonstrated using a case study. Methods are also presented for copula selection and estimation of the copula parameters.
Proceedings of the Canadian Engineering Education Association (CEEA)
– Lifelong learning might be one of the most important attributes for students pursuing a profe... more – Lifelong learning might be one of the most important attributes for students pursuing a professional degree, e.g. medicine, law or engineering. From teaching and assessment point of view, it may be one of the most challenging attributes. In engineering programs, it is one of the required graduate attributes identified by the Canadian Engineering Accreditation Board (CEAB), the Accreditation Board for Engineering and Technology (ABET) in the USA and other accreditation bodies around the world. In this article we present a laboratory procedure to teach and assess lifelong learning in an engineering program. The concept of lifelong learning as defined by different accreditation bodies is discussed first and corresponding learning outcomes are developed using the revised Bloom’s taxonomy. Student activities required to achieve the outcomes are then devised. The links between pre-, in- and post-lab activities and the learning outcomes are established and the approach to run a laborat...
Proceedings of the Canadian Engineering Education Association, 2015
An “expert-follower” approach toconduct laboratory courses is outlined in this article. Themain o... more An “expert-follower” approach toconduct laboratory courses is outlined in this article. Themain objective of the proposed procedure is to enhancegraduate attributes. Two important attributes namely,investigation and team work are focused. In this setting,one team becomes the designated expert team for anexperiment. Based on the range of operating conditions ofequipment, the expert team will decide different sets ofexperimental conditions. The expert team will first run theexperiment and the follower teams will run in thefollowing weeks, each at a different set of conditions. Thefollower teams will be briefed by the expert team prior toand during the experiment. The expert team will gatherdata from the follower teams every week. Each team willbe designated expert for one experiment while followerfor the others. The expert team will have a large set ofdata to investigate the characteristics of thecorresponding equipment. They will have to analyze data,identify any abnormality and prob...
Lifelong learning might be one of the most important attributes for students pursuing a professio... more Lifelong learning might be one of the most important attributes for students pursuing a professional degree, e.g. medicine, law or engineering. From teaching and assessment point of view, it may be one of the most challenging attributes. In engineering programs, it is one of the required graduate attributes identified by the Canadian Engineering Accreditation Board (CEAB), the Accreditation Board for Engineering and Technology (ABET) in the USA and other accreditation bodies around the world. In this article we present a laboratory procedure to teach and assess lifelong learning in an engineering program. The concept of lifelong learning as defined by different accreditation bodies is discussed first and corresponding learning outcomes are developed using the revised Bloom's taxonomy. Student activities required to achieve the outcomes are then devised. The links between pre-, in-and post-lab activities and the learning outcomes are established and the approach to run a laborato...
This paper presents a new integrated methodology for fault detection and diagnosis. The methodolo... more This paper presents a new integrated methodology for fault detection and diagnosis. The methodology is built using the multivariate exponentially weighted moving average principal component analysis (MEWMA-PCA) and the Bayesian network (BN) model. The fault detection is carried out using the MEWMA-PCA; diagnosis is completed utilizing the BN models. A novel supervisory learning-based methodology has been proposed to develop the BNs from the historical fault symptoms. Although the algorithm has been extensively applied to the Tennessee Eastman (TE) chemical process, monitoring of three specific (difficult to observe) faults, IDV 3, IDV 9, and IDV 15, has been demonstrated in this article. Most of the existing data-based methods have faced the challenge to detect these faults with a good detection rate (DR). Hence, these faults have been reported as either unobservable or strenuous to detect. Overall, fault detection performance of the squared prediction error (SPE) statistics combined with the MEWMA-PCA wa...
An output error optimization approach for identification of parsimonious fractional order models ... more An output error optimization approach for identification of parsimonious fractional order models using multi-frequency sinusoids as input is proposed. The algorithm simultaneously estimates orders, parameters and the delay of simple models with fractional orders using the Gauss-Newton optimization approach. Optimization-based methods for fractional order model identification require evaluation of the sensitivity functions which include the logarithmic derivatives of the input signal. In the existing literature, central difference or similar methods are used to numerically calculate the Jacobian matrix due to difficulties with numerical simulation of the logarithmic derivatives. We assume deterministic input signals and provide analytical expressions for the logarithmic derivatives of single and multiple frequency sinusoids. Relevant mathematical derivations are presented and the analytical expressions are used to evaluate the Jacobian. Effects of noise to signal ratio, input frequen...
International Journal of Pressure Vessels and Piping
Abstract This paper presents a predictive probabilistic model to estimate the overall economic im... more Abstract This paper presents a predictive probabilistic model to estimate the overall economic impacts of pitting corrosion by considering both the corrosion costs and significant losses that may occur if failures occur because of pitting corrosion. The major loss categories are considered as business loss and accidental loss. Models are proposed to estimate the elements in each loss category. Corrosion prevention, monitoring, maintenance and management (CPM3) costs are considered as the main categories of corrosion costs and the probabilistic models are proposed to estimate these costs. The Monte Carlo (MC) method is used to integrate the loss and cost models and also to address the uncertainties in these models. The effect of inflation on loss values and the mitigating impact of CPM3 costs are also taken into consideration in the developed models. The application of the proposed risk model is demonstrated using a piping case study. As highlighted in the case study, the developed models help to assess corrosion economic risk, which is used for corrosion prevention and control's decision-making.
The Canadian Journal of Chemical Engineering, 2016
An overview of identification of continuous-time models from step responses using the integral eq... more An overview of identification of continuous-time models from step responses using the integral equation approach is presented. Both open loop and closed loop identification as well as identification of multiple-input-multiple-output (MIMO) models are considered. Solutions to practical implementation problems are provided and methods for identification with transient initial conditions using raw data as well as estimation algorithms in the presence of disturbances are outlined. The methodologies are presented in a simplified way using the example of a first order model; however, the algorithms are applicable for models with higher orders. Solution techniques for the estimation equations are also discussed. Identification results under different experimental conditions and data quality are presented to demonstrate the performance of the algorithms. A number of experimental and simulation examples are presented to demonstrate the applicability of the approach. This article is protected by copyright. All rights reserved
Alarm flooding is a significant problem in the process industries. To solve this problem, a scena... more Alarm flooding is a significant problem in the process industries. To solve this problem, a scenario-based early warning system design methodology is proposed. It comprises three steps: (i) scenario identification: events are identified by HAZOP analysis, variables are allocated to the scenario-based group, and the variables states correlated to the scenarios are identified; (ii) model development: Bayesian network of all variables is learned from the process data, and the events nodes are appended according to expert knowledge to construct the Bayesian network model of a scenario-based early warning system; (iii) model implementation: the model is applied online to monitor process, the monitored variables continuously produce evidence, update the events probabilities, find the root causes, and give an events warning message together with the root cause to operators. The methodology implementation and salient points are explained with the help of an easy to follow simple case study.
Process safety and risk assessment are often multidimensional and hence require the joint modelin... more Process safety and risk assessment are often multidimensional and hence require the joint modeling of several potentially correlated random variables. Any effort to address the correlation among the input variables is important and could improve the accuracy in practical applications of risk assessment models. This paper discusses the problems with correlated variables used in risk assessment and presents a copula-based technique to model dependency among variables to improve uncertainty analysis. Using the copula approach, capturing the dependence structure among different risk factors and estimating the univariate risk marginals can be separated. This advantage simplifies the overall risk estimation for systems with multiple dependent risk sources. The advantage of the copula-based framework for generalization over the traditional correlation analysis technique is demonstrated using a case study. Methods are also presented for copula selection and estimation of the copula parameters.
Proceedings of the Canadian Engineering Education Association (CEEA)
– Lifelong learning might be one of the most important attributes for students pursuing a profe... more – Lifelong learning might be one of the most important attributes for students pursuing a professional degree, e.g. medicine, law or engineering. From teaching and assessment point of view, it may be one of the most challenging attributes. In engineering programs, it is one of the required graduate attributes identified by the Canadian Engineering Accreditation Board (CEAB), the Accreditation Board for Engineering and Technology (ABET) in the USA and other accreditation bodies around the world. In this article we present a laboratory procedure to teach and assess lifelong learning in an engineering program. The concept of lifelong learning as defined by different accreditation bodies is discussed first and corresponding learning outcomes are developed using the revised Bloom’s taxonomy. Student activities required to achieve the outcomes are then devised. The links between pre-, in- and post-lab activities and the learning outcomes are established and the approach to run a laborat...
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