- Newfoundland and Labrador, Canada
Salim Ahmed
Memorial University of Newfoundland, Process Engineering, Faculty Member
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.... 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 professional degree, e.g. medicine, law or engineering. From teaching and assessment point of view, it may be one of the most challenging attributes.... 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...
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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... 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...
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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... 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...
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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... 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.
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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... 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
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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... 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.
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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... 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.
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– 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... 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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Most existing risk management models for process industries do not consider the effect of insurance coverage, which results in an overestimation of overall risk. A model is presented in this article to study the effect of insurance... more
Most existing risk management models for process industries do not consider the effect of insurance coverage, which results in an overestimation of overall risk. A model is presented in this article to study the effect of insurance coverage of health, safety, environmental, and business risks. The effect of insurance recovery is modeled through the application of adjustment factors by considering the stochastic factors affecting insurance recovery. The insurance contract's conditions, deductibles, and policy limits are considered in developing the insurance recovery adjustment factors. Copula functions and Monte Carlo simulations are used to develop the distribution of the aggregate loss by considering the dependence among loss classes. A case study is used to demonstrate both the practical application of the proposed insurance model to improve management decisions, and the mitigating effect of insurance to minimize the residual risk.
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Teamwork might be considered as one of the most desired attributes of engineering graduates. From anassessment perspective, it might be one of the most difficult attributes to assess. Evaluation of teamworkrefers to the assessment of... more
Teamwork might be considered as one of the most desired attributes of engineering graduates. From anassessment perspective, it might be one of the most difficult attributes to assess. Evaluation of teamworkrefers to the assessment of individuals on their ability to work in a team. However, in many cases theperformance of the team is taken as the only measure of teamwork. A plethora of literature has beendedicated to the understanding of the attribute; nevertheless, many laboratory instructional team facesthe dilemma on whether the designed assessment meet its requirements. In this article, the concept ofteamwork will be explored in the context of engineering laboratories. Following an exploratoryunderstanding of the attribute, mechanism to assess teamwork will be proposed. The attribute will bedecomposed into component skills and each skill element will be explored to determine assessmentrequirement by answering to a series of what, when and how questions. The outcome if the work wi...
In undergraduate laboratory courses, students often perform experiments by following standard procedures designed by the instructors or outlined in the laboratory manuals. The calculation procedures are also provided to estimate certain... more
In undergraduate laboratory courses, students often perform experiments by following standard procedures designed by the instructors or outlined in the laboratory manuals. The calculation procedures are also provided to estimate certain parameters using experimental data. Finally they report the findings from the experiments. These activities lead to anumber of different learning outcomes and students achieve a number of attributes. They gain experience with problem analysis, use of engineering tools, investigation and communication which are identifiedas required graduate attributes by the Canadian Engineering Accreditation Board. However, the important aspect of design that may be achieved through the development of structured experimental procedure remains unattended. In this article we discuss an approach for undergraduate laboratory experiments to enhance the attributes of engineering graduates. In this approach students are not provided with the experimental procedure; instead...
This paper presents a layout optimization methodology for the topside deck of a floating liquefied natural gas facility (FLNG) using inherent safety principles. Natural gas is emerging as a clean energy, and a large amount of natural gas... more
This paper presents a layout optimization methodology for the topside deck of a floating liquefied natural gas facility (FLNG) using inherent safety principles. Natural gas is emerging as a clean energy, and a large amount of natural gas exists in the proven offshore area, thus making it an energy source with huge potential in today's and the future market. FLNG facilities tap natural gas from an offshore well by floating, compressing it into liquefied natural gas (LNG), and offloading it to LNG carriers after temporary storage. In addition, FLNG facilities enable long-distance as well as multilocation transportation. The FLNG facility requires compact design due to limited space and high construction costs and thus faces a more challenging situation where the design has to concurrently guarantee economic profits and a safe operational environment. Therefore, the layout of the topside deck, which includes production, storage, and other functions, plays a paramount role in design...
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Research Interests: Mechanical Engineering, Chemical Engineering, Monte Carlo Simulation, Modeling, Algorithm, and 10 moreModel validation, Change detection, Time Delay, Chemical Engineering Science, Continuous Time Models, Experimental Data, Monte Carlo Method, Multiple Input Multiple Output, Continuous time, and Discrete time
ABSTRACT In this work, the concept of loss functions is incorporated in the design of a risk-based early warning system for process facilities. This approach allows considering the effects of process deviations from its target operating... more
ABSTRACT In this work, the concept of loss functions is incorporated in the design of a risk-based early warning system for process facilities. This approach allows considering the effects of process deviations from its target operating conditions on potential loss from both safety and product quality point of view. Inverted beta loss function is used to describe the consequences of process deviations. The developed loss function-based consequence analysis approach is combined with a process variability dependent probability assessment method and the process safety time to estimate the risk. The algorithm continuously evaluates the risk associated with the current state of a process and issues warnings based on the estimated risk. The warnings are further categorized into alerts and alarms, resulting in reduction of the possibilities of alarm floods. The proposed integrated model will allow a systematic annunciation, prioritization and analysis of warnings using estimated risk and thus will be a valuable tool to ensure a safe and cost effective operation of a process facility. The applicability of the proposed procedure is demonstrated using the example of a continuous stirred tank reactor.
Abstract A two stage algorithm for parameter and delay estimation of continuous-time transfer function models from sinusoidal response is presented. In the first stage, a step response of the process is estimated from its sinusoidal test... more
Abstract A two stage algorithm for parameter and delay estimation of continuous-time transfer function models from sinusoidal response is presented. In the first stage, a step response of the process is estimated from its sinusoidal test data. The input may be single ...
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ABSTRACT This paper presents probabilistic models to estimate business losses due abnormal situations in process facilities. The main elements of business loss are identified as business interruption loss and reputational loss. The... more
ABSTRACT This paper presents probabilistic models to estimate business losses due abnormal situations in process facilities. The main elements of business loss are identified as business interruption loss and reputational loss. The business insurance interruption approach is used to model business interruption loss. The elements of business interruption loss are modeled based on expert knowledge using Program Evaluation Review Technique (PERT), which are then integrated using the Monte Carlo (MC) simulation approach. The reputational loss is considered Weibul distributed and the parameters are estimated by applying a scenario-based approach. Copula functions are then used to develop the distribution of the aggregate loss, considering the correlation between business interruption and reputational losses. The application of the loss models is demonstrated using a distillation column case study. The models presented here provide a mechanism to monitor process facility’s business performance, with associated uncertainties, and to make swift operational and safety decisions. This will help to improve process facilities safety performance and optimal allocation of resources where they are needed the most.
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ABSTRACT Pitting corrosion is a localized corrosion that often causes leak and failure of process components. The aim of this work is to present a new fitness-for-service (FFS) assessment methodology for process equipment to track and... more
ABSTRACT Pitting corrosion is a localized corrosion that often causes leak and failure of process components. The aim of this work is to present a new fitness-for-service (FFS) assessment methodology for process equipment to track and predict pitting corrosion. In this methodology, pit density is modeled using a non-homogenous Poisson process and induction time for pit initiation is simulated as the realization of a Weibull process. The non-homogenous Markov process is used to estimate maximum pit depth, considering that only the current state of the damage influences its future development. Subsequently, the distributions of the operating pressure and the estimated burst pressure of the defected component are integrated with Monte Carlo simulations and First Order Second Moment (FOSM) method to calculate the reliability index and probability of failure. This methodology provides a more realistic failure assessment and enables consideration of uncertainty associated with estimating pit characteristics. The practical application of the proposed model is demonstrated using a piping case study.
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ABSTRACT This study presents an overall loss modelling methodology for process facilities. The methodology comprises loss scenario identification and aggregation of losses due to process deviations. The identification of loss scenarios... more
ABSTRACT This study presents an overall loss modelling methodology for process facilities. The methodology comprises loss scenario identification and aggregation of losses due to process deviations. The identification of loss scenarios and determination of the time periods at which a process experiences each scenario are described first. Then, the application of the copula functions and their integration with the Monte Carlo (MC) approach are proposed to address the existing challenge of loss aggregation for multiple-loss scenarios. The proposed loss aggregation provides a flexible and realistic approach to construct joint multivariate distribution of the losses by considering their interdependence. The sensitivity of the model to the choice of correlation parameters is investigated. The results serve as a reminder to risk analysts about the significance of choosing an appropriate loss aggregation model for risk analysis purposes. The application of the methodology is demonstrated using a distillation column case study.
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ABSTRACT A three dimensional computational fluid dynamics (CFD) simulation of liquefied natural gas (LNG) pool fire has been performed using ANSYS CFX-14.The CFD model solves the fundamental governing equations of fluid dynamics, namely,... more
ABSTRACT A three dimensional computational fluid dynamics (CFD) simulation of liquefied natural gas (LNG) pool fire has been performed using ANSYS CFX-14.The CFD model solves the fundamental governing equations of fluid dynamics, namely, the continuity, momentum and energy equations. Several built-in sub-models are used to capture the characteristics of pool fire. The Reynolds-Averaged Navier-Stokes (RANS) equation for turbulence and the eddy-dissipation model for non-premixed combustion are used. For thermal radiation, the Monte Carlo (MC) radiation model is used with the Magnussen soot model. The CFD results are compared with a set of experimental data for validation; the results are consistent with experimental data. CFD results show that the wind speed has significant contribution on the behavior of pool fire and its domino effects. The radiation contours are also obtained from CFD post processing, which can be applied for risk analysis. The outcome of this study will be helpful for better understanding of the domino effects of pool fire in complex geometrical settings of process industries.
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Abstract Over the last few years many important issues in continuous-time identification from step response have been addressed. Methods for simultaneous estimation of the delay and algorithms to deal with transient initial conditions... more
Abstract Over the last few years many important issues in continuous-time identification from step response have been addressed. Methods for simultaneous estimation of the delay and algorithms to deal with transient initial conditions have been proposed. However, the ...
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ABSTRACT Development of natural resources in harsh environments presents significant technical and logistical challenges. An industrial workshop on “safety and integrity management of operations in harsh environments” was organized by the... more
ABSTRACT Development of natural resources in harsh environments presents significant technical and logistical challenges. An industrial workshop on “safety and integrity management of operations in harsh environments” was organized by the safety and risk engineering group at Memorial University of Newfoundland to bring together industrial practitioners, regulatory authorities, and research and development institutions to identify the safety and integrity challenges in harsh environments, share experience, and develop a roadmap for desired solutions. This article summarizes the lessons learned from the workshop on safety issues in harsh environments. The workshop identified that there are safety challenges regarding construction and operation including a lack of detailed standards, optimization with respect to winterization, and data scarcity. The remoteness of operations in harsh environments is an additional challenge. Finally, human factors add another set of challenges that arise from the physical and psychological behavior of personnel in harsh and remote environments. © 2014 American Institute of Chemical Engineers Process Saf Prog, 2014
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ABSTRACT Process deviations, along with failure of control systems and protection layers, result in safety and quality loss in plant operations. This paper proposes an operational risk-based warning system design methodology based on... more
ABSTRACT Process deviations, along with failure of control systems and protection layers, result in safety and quality loss in plant operations. This paper proposes an operational risk-based warning system design methodology based on overall system loss. Loss functions are used to define the relationship between process deviations and system loss. For this purpose, properties associated with quadratic loss function and a set of inverted probability loss functions are investigated and compared. The results suggest that loss functions can be used in a novel way to assess operational stability and system safety. The proposed consequence assessment methodology using loss functions is then incorporated into a risk-based warning system design model to analyze warnings associated with process deviations. A simulated case study is presented to demonstrate potential application of the proposed methodology; the study examines the response to a temperature surge for a reactor system.
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A simple method for identifying parameters for integrating processes with deadtime and inverse response has been presented. Explicit expressions for the identification parameters have been derived. These expressions involve numerical... more
A simple method for identifying parameters for integrating processes with deadtime and inverse response has been presented. Explicit expressions for the identification parameters have been derived. These expressions involve numerical integration. The present method ...
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A systems approach to design, analyze and prioritize alarms is proposed. By a system, we refer to a set of variables within a process. An alarm is activated based on the risk associated with the state of the variables in a system. The... more
A systems approach to design, analyze and prioritize alarms is proposed. By a system, we refer to a set of variables within a process. An alarm is activated based on the risk associated with the state of the variables in a system. The objectives are to integrate ...
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Alarm flooding is a major safety issue in today's processing facilities. Important recommendations are available for alarm management; however, they are often violated in practice, especially in the alarm systems implemented through... more
Alarm flooding is a major safety issue in today's processing facilities. Important recommendations are available for alarm management; however, they are often violated in practice, especially in the alarm systems implemented through the distributed control system. An effective process alarm prioritization and management system is desired for a safe and effective operation of a process facility.In present work, authors address