Browsing by Author "Dai, Liming"

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Open Access
Active Nonlinear Vibration Control of Engineering Structures of Multiple Dimensions
(Faculty of Graduate Studies and Research, University of Regina, 2015-03) Sun, Lin; Dai, Liming; Henni, Amr; Mobed, Nader; Suh, C. Steve
An active nonlinear mechanical vibration control strategy is developed in the research of the author’s PhD program for the nonlinear vibration control of engineering structures of multiple dimensions. The proposed control strategy has been applied in several wildly applied typical engineering structures, including Euler-Bernoulli beams and axially moving structures. Nonlinear vibrations wildly exist in engineering structures, such as bridge, aircrafts, micro-electro-mechanical devices, and elevator cables. Comparing to linear vibrations, nonlinear vibrations may lead structure failures in short time, and chaotic vibrations among the nonlinear vibrations features unpredictability. Considering the damage and unpredictability of nonlinear vibrations, nonlinear vibrations is ought to be controlled. However, most of the existing active nonlinear vibration control strategies can only be applied to the nonlinear dynamic system of single dimension, while multi- dimensional dynamic systems show the advantages over those of single dimension in dynamic analysis. Therefore, an active nonlinear control strategy has been proposed based on the existing control strategy the Fuzzy Sliding Mode Control (FSMC) strategy, and has been applied in the vibration control of the following engineering structures: Euler-Bernoulli beams subject to external excitation; axially moving Euler-Bernoulli beam without external excitation; retracting Euler-Bernoulli beam without external excitation; axially translating cable; extending nonlinear elastic cable. First of all, the nonlinear vibration and control of an Euler-Bernoulli beam subjected to a periodic external excitation is given as an example to demonstrate how the active nonlinear control strategy is developed and applied for a multi-dimensional nonlinear dynamic system. Then, considering the two typical engineering structures modeled with Euler-Bernoulli beams, the control strategy is applied in the nonlinear vibration control of a micro-electro-mechanical system (MEMS) beam and a fluttering beam. After that, corresponding to the attentions paid to the axially translating materials, the control strategy is applied in the nonlinear vibration control of four typical axially moving structures. Applications of the proposed control strategy evidently show effectiveness and efficiency of the active control strategy in controlling the nonlinear vibrations of typical engineering structures.
Open Access
Analysis of Impact Factors for Traffic Noise in urban Areas
(Faculty of Graduate Studies and Research, University of Regina, 2014-12) Huang, Kai; Dai, Liming; Henni, Amr; Mehrandezh, Mehran; Mobed, Nader
Road traffic noise contributes significantly to outdoor environmental noise, especially in urban areas. The pressure of traffic noise is influenced by many factors such as types of engines, exhaust systems and tires interacting with the road, weather and road conditions. The tire/pavement interaction noise has been proven to be the major source of the traffic noise, especially for cruising driving conditions, which is highly influenced by surface characteristics of road pavement. Traffic flow is also a factor – apart from vehicles, tires and road surface characteristics – in affecting traffic noise pressures. The noise level can increase by about 3 dBA when traffic flow doubles, if the traffic composition, speed and driving patterns are constant. Consequently, it is required to investigate the effects of road pavement conditions and traffic flow on traffic noise emission, and further explore the interactive effect of operation time of pavement and traffic flow for traffic noise control and mitigation. In this research, a series of field experiments are conducted on highways of new and old pavements. The variations of traffic flow and traffic noise pressure levels together with the functional relationships between them are analyzed based on the noise data collected from the highways in an urban area. With the collected data, the maximum traffic flow and traffic noise pressure levels are determined in a specified time manner. Logarithmic functional relationships are found between traffic noise pressure level and traffic flow for both old and new pavements. It is also found that the improvement in pavement material of highway may promote the absorption of traffic noise. A single value index is developed for quantitatively and conveniently evaluating the acoustic quality of highways. The findings in this research may give some inspiration for construction and management of low noise highways. The field experiment is expanded to the year of 2014, with the road near the measurement sites repaved in 2013. The results indicate that the re-pavement of road surface can effectively reduce the traffic noise. However, as the road surface ages, such reduction effect would also decrease. Additionally, an entropy-copula method is proposed for modelling dependence between traffic flow and traffic noise on the Trans-Canada Highway (#1 highway of Canada) in the City of Regina based on the field experiment measurements. The proposed entropy-copula method combines the maximum entropy and copula methods into a general framework, in which the marginal distributions of traffic flow and traffic noise are estimated through the principle of maximum entropy (POME) theory, and the joint probabilities are derived through the Gaussian and Student t copulas. The proposed method is applied at two field experiment sites on the Trans-Canada Highway. Based on the K-S and A-D tests and RMSE value, the entropy method shows well performance in quantifying the probability distributions of traffic flow and traffic noise. Meanwhile, both Gaussian and Student t copulas can well model the joint probability distributions for traffic flow and traffic noise at both experiment sites, which are demonstrated by the Cramér von Mises statistics and the RMSE values. Furthermore, the conditional CDFs of the traffic noise at two experiment sites are derived based on the established Gaussian and Student t copulas under different traffic flow scenarios. The obtained conditional CDFs indicate positive structures between traffic flow and traffic noise at both experiment sites. II
Open Access
Application of data-driven and physics-driven models in predicting vibratory responses of nonlinear dynamic systems
(Faculty of Graduate Studies and Research, University of Regina, 2024-06) Wang, Luyao; Dai, Liming; Mehrandezh, Mehran; Aroonwilas, Adisorn; Chen, Zengtao
The investigation of chaotic vibrations is essential for understanding the vibro-responses of engineering structures subjected to external excitations. This understanding is crucial for developing advanced strategies to control chaotic structural instability and sensitivity. Traditional methods for investigating chaotic vibration behavior rely on physics-based model establishment, where physical models are mathematically analyzed through complex calculations of differential equations. Although the development of analytical and numerical theories is relatively mature, the costly human labor required for feature engineering and high demands for expert knowledge in mathematical and physical domains limit its application in engineering fields to a certain extent. Therefore, this research aims to establish an innovative approach for predicting the chaotic responses of nonlinear models in the engineering field by proposing data-driven models to accomplish supervised learning regression tasks. The application of these proposed data-driven models in predicting chaotic responses of various nonlinear system models is conducted in a completely data-driven and non-intrusive manner. This thesis implements prediction tasks for chaotic vibrations of different types of nonlinear dynamic systems based on both physics-driven and data-driven models. These nonlinear systems serve as fundamental reference models and are widely applied in various engineering fields. Specifically, the physics-based investigations in this work focus on comparing the advantages of the developed P-T method over the 4th-order Runge-Kutta method in terms of accuracy and reliability. Additionally, studies on chaotic vibration prediction based on data-driven models are also carried out in this thesis. Three hybrid neural networks are proposed, and their architectures are thoroughly explained. The effectiveness and robustness of these models are sequentially enhanced. Specifically, their ability to handle chaotic sequences has evolved from considering temporal correlations to considering spatiotemporal correlations, and their capability to manage the length of inputs and outputs has progressed from fixed to variable. Besides the inherent advantages of data-driven investigation compared to physics-driven methods, the superior performance of the proposed data-driven models over conventional benchmarks in terms of training time and testing loss is quantitatively demonstrated. The continuous development of measuring equipment has facilitated easier access to substantial high-quality data. Thus, the findings of this research provide new insights into the investigation of chaotic responses and are valuable for analyzing and understanding chaotic vibrations with greater efficiency. The optimized results obtained in this research are expected to offer practically sound guidance for optimizing engineering structural design and enhancing performance when considering chaotic or nonlinear vibrations.
Open Access
BIOWINTM Modeling of the Startup of an Anaerobic Digester Used in Wastewater Treatment Plants
(Faculty of Graduate Studies and Research, University of Regina, 2013-03) Yang, Wenwen; Young, Stephanie; Chan, Christine; Huang, Guo H.; Dai, Liming; Shirif, Ezeddin; Bayer, Sean
Anaerobic digestion involves biochemical and physiochemical processes. It is an effective process for sludge stabilization and methane gas production. However, the digester capacity decreases with time due to the buildup of solid deposits at the bottom of the digester. Therefore, routine shutdown and cleanup are commonly practiced at Wastewater Treatment Plants (WWTPs). Currently, WWTP operators face the challenge of starting up an anaerobic digester in a timely, cost-effective manner with effective methane gas production. This challenge can be addressed by computer modeling and simulations of different operating conditions, which is a cost-effective solution in comparison to experimentation. In this research, the commercially available BioWinTM software was used to build an Anaerobic Digestion Model (BioWinTM model) for the simulation of the startup of an anaerobic digester. BioWinTM dynamic simulations were conducted under different operating conditions to determine optimal seed sludge volume, sludge feed rate, and bicarbonate concentration to be used during the digester startup. Strategies for a timely and cost-effective startup using the minimum amount of available seed sludge and primary sludge feed were developed, based on the results of dynamic simulations conducted using field data gathered from the Regina WWTP. The result of this research was to decrease digester startup time and operational costs while increasing methane gas production. This will provide significant economic and environmental benefits, especially for WWTPs currently facing digester startup challenges, limited sludge treatment capacities, and low methane gas production.
Open Access
Celebration Of Authorship Program 2016-2017
(University of Regina Library, 2017) Ackerman, Jennifer; Ackerman, Katrina; Anderson, Robert; Arnal, William; Aziz, Madina; Blake, Raymond; Blakley, Janelle; Coleman, Cory; Dai, Liming; DeSantis, Gloria; Diaz, Joshua; Doke Sawatzky, Katie; Engel, Brenna; Gane, David; Gidluck, Lynn; Gottselig, Jared; Grant, Trevor; Grimard, Celine; Jaffe, JoAnn; Johnson, Dale; Juschka, Darlene; Kikulwe, Daniel; Hillabold, Jean; Mah, Jeannie; Marroquin, Rebbeca; McDonald, Anne; Meehan SJ, John; Nzunguba, lbio; Pete, Shauneen; Pirbhai-Illich, Fatima; Powell, Marie; Russell, Gale; Shami, Jeanne; Solomon, Michaela; Stringer, Kyrsten; Taylor, Caitlin; Triggs, Valerie; Vetter, Mary
Open Access
Design, Development, and Human Analogous Control of a Climbing Robot
(Faculty of Graduate Studies and Research, University of Regina, 2012-03) Bazargan, Amirhossein; Mehrandezh, Mehran; Dai, Liming; Aroonwilas, Adisorn; Mayorga, Rene; Paranjape, Raman
In this thesis, a re-configurable wheeled climbing robot has been introduced. This robot is capable of doing a multitude of tasks that no other single robot could do in the past. It can climb staircases, move inside empty ducts and pipes, climb up ropes and poles of varying cross sections, and even jump over obstacles with proper motion coordination. It can also move inside narrow passageways by reconfiguring itself. The design of a re-configurable robot capable of traversing a wide range of unconventional terrains is the novelty in this invention. A comprehensive dynamic model of the robot is derived for the first time. A real-time simulator to try different control strategies by a human operator using conventional human-machine interfaces has been developed. This simulator can be employed to size the electromechanical actuators and to synthesize different control strategies in a short time. The data obtained can be also used to design a human-analogous autonomous controller. After outline of the theory, background and applications of soft computing techniques for system construction and control including Artificial Neural Networks (ANN), Fuzzy Logic Control (FLC), and the Adaptive Neuro-Fuzzy Inference Systems (ANFIS), a novel human-analogous control strategy based on ANFIS was implemented to control the position of the robot climbing a straight pole against gravity. The design process of the ANFIS-based human-analogous control strategy includes the following steps: First, a human expert tries to control the real system in real time within a human-in-the-loop simulator via a Human-Machine Interface (HMI) using sensory information obtained from visual tracing in the HMI in real time from the real system. The control task is done by using a control interface (i.e., a joystick). Relevant input/output data is stored, filtered, and used offline to tune the parameters of an ANFIS-based controller. The ANFIS controller whose parameters have been optimized is then implemented on the real system autonomously. Based on the information obtained via the HITL simulator system, the controller can extrapolate needed data for untrained cases.
Open Access
Development of Characterization and Optimization Methodologies for Waste Management
(Faculty of Graduate Studies and Research, University of Regina, 2012-07) Sun, Wei; Huang, Guo H.; Dai, Liming; deMontigny, David; Yang, Xuedong; Baetz, Brian W.
Applications of mathematical models to waste management are usually complicated by the complexities involved in either waste treatment processes or waste management systems. In this dissertation research, a set of characterization and optimization methodologies have been developed and applied to waste management. In detail, they include: (a) a stepwise-cluster microbial biomass inference (SMI) model through introducing stepwise cluster analysis (SCA) into composting process modeling for tackling the nonlinear relationships between state variables and microbial activities; (b) a genetic algorithm (GA) aided stepwise cluster analysis (GASCA) method for describing the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting; (c) an inexact piecewise quadratic programming (IPQP) model through coupling piecewise linear regression with interval-parameter quadratic programming for handling the nonlinear objective function in waste allocation planning; (d) an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model was developed to tackle nonlinear economies-of-scale (EOS) effects in intervalparameter constraints for a representative waste management problem; and (e) an inexact joint-probabilistic left-hand-side chance-constrained programming (IJLCP) method for reflecting the inexact relationships between amounts of waste transported and treated effectively. In terms of methodologies, the major contribution of this research includes: the SCA was for the first time, introduced into mapping the relationships in composting processes; the GASCA combining GA with SCA would possess abilities in both variable searching and nonlinear fitting; the IPQP and IPFP models were designed through introducing concepts of piecewise linearization to the related inexact programming methods; and a non-equivalent but sufficient linearization form for the IJLCP model was proposed and proved straightforwardly. In terms of applications, the major contribution involves: (a) based on the SCA and GASCA trees, the effects of the state variables on thermophilic bacteria, mesophilic bacteria, and the C/N ratio were quantified; (b) the applications of IPQP and IPFP implied that the often ignored EOS effects should be considered in the real-world waste management system to obtain accurate net system costs; and (c) the IJLCP’s application indicated that a higher joint probability level would result in a lower system costs in a waste management system.
Open Access
Development of Experimental and Modelling Approaches to Characterize Noise Reduction Capability of Porous Materials
(Faculty of Graduate Studies and Research, University of Regina, 2019-07) Huang, Kai; Dai, Liming; Mehrandezh, Mehran; Morgan, Yasser; Mobed, Nader; Lou, Haiye
Porous materials have been recognized as effective materials for noise reduction and noise control. It is also recognized that numerous inherent and external factors may affect the noise reduction properties of porous materials. The research of this dissertation aims to develop innovative experimental and modelling approaches to analyze the noise reduction capability of porous materials under different conditions and to study the main factors affecting the noise reduction capability of porous materials. The impact of material age on noise reduction properties of porous materials is first studied, and a Nested Ensemble Filtering (NEF) approach is proposed for parameter estimation and uncertainty quantification in traffic noise emission from porous pavements. The proposed NEF method improves upon the ensemble Kalman filter (EnKF) method by incorporating sample importance resampling (SIR) procedures into the EnKF update process. Applying the proposed NEF method to traffic noise prediction on the Trans-Canada Highway in the City of Regina, the results indicate: (a) the NEF method provides accurate parameter estimation in the traffic noise prediction model; (b) the uncertainty in the traffic noise model can be significantly reduced and quantified through the proposed NEF approach; and (c) the unit noise emission for new porous pavement is significantly decreased in comparison with that of old pavement considered, regardless of the impacts of uncertainties. In addition to porous material age, air density within pore structures also impacts acoustic properties of porous materials. Consequently, a series of experimental investigations are conducted to investigate the effects of different levels of vacuum on the sound reduction and acoustic properties of porous materials. An innovative experiment would be designed to measure acoustic responses, such as sound intensities and corresponding frequencies, for various porous materials under different vacuum levels. The results indicate that applying even relatively low vacuum levels to porous materials has a significant effect on sound reduction. The sound absorption coefficients for various porous materials under different vacuum levels are further characterized through the statistical energy analysis (SEA) approach. It is anticipated that the research findings in this research may lead to the construction of effective sound reducing products for attenuating noise, increasing insertion loss or improving sound insulation. In order to comprehensively evaluate the applicability of porous-structured noise control (PSNC) measures, a systematic evaluation framework is to be proposed to identify the most appropriate PSNC options under consideration of both internal and external factors. Such a framework is based on an inexact fuzzy integer chance constraint programming (IFICCP) approach to integrate the acoustic properties of each measure (i.e. reduction rate), unit cost, installation location and environmental tolerance into a general framework. Also, the IFICCP method can handle uncertainties expressed as fuzzy and interval numbers in the noise control system established with various porous materials. A number of decision alternatives have been obtained for each acceptable noise level and analyzed under various fuzzy confidence levels. They can potentially reflect complex tradeoffs among cost and properties of porous materials, location, and environmental considerations, and further provide decision support to find the most desirable porous materials for noise reduction.
Open Access
Development of Inexact Optimization Methods for Planning Environmental Management Systems Under Multiple Uncertainties
(Faculty of Graduate Studies and Research, University of Regina, 2014-12) Zhai, Yuanyuan; Huang, Guo H.; Ng, Tsun Wai Kelvin; An, Chunjiang; Dai, Liming; Yao, Yiyu
Environmental planning is becoming a key component in environmental management due to rapid socio-economic development and steadily increasing population. In real-world applications, uncertainties and complexities are frequently involved in environmental management systems, where decision makers need sound management approaches in order to allocate their limited resources to different competing end users. Thus, more innovative approaches are required to deal with multiple uncertainties. As well more in-depth information in regard to the individual and interactive effects among multiple input parameters on the system performance is needed. In this research, a dual-interval two-stage mixed-integer inexact-chance-constrained linear programming (DITMIC) method was developed for the planning of flood-diversion management systems. DITMIC did not only reflect uncertainties expressed as intervals, dual intervals, interval-valued probability distributions but also incorporated pre-regulated diversion policies into its optimization process. Various policy scenarios were generated and they were associated with varied economic penalties if the promised targets were violated. Furthermore, DITMIC assisted in analyzing dynamic features of capacity-expansion schemes when it came to decision-making. Various flood-diversion patterns and capacity-expansion schemes were obtained under different risk levels. The reliability of satisfying the system constraints under uncertainty was also examined. This enabled decision makers to choose the most desired outcome relative to their preference and perception of future conditions. To better enable insights on the detailed effects from uncertain parameters as well as their interactions on the system objective, a factorial dual-interval programming (FDIP) method was developed for planning municipal waste management systems. Through the integration of factorial analysis and dual-interval linear programming into a general framework, the FDIP method could handle uncertainties existing in the left- and right-hand sides of the objective function, as well as in the associated constraints. Moreover, it had the advantages of identifying influential parameters along with their joint effects on the system output. Impact factors as well as their interactive effects have been identified and analyzed for the lower and upper bounds of the system output, which could further provide valuable information on their effects on the system solutions when it came to decision-making.
Open Access
Development of Inexact T2 Fuzzy Optimization Approaches for Supporting Energy and Environmental Systems Planning Under Uncertainty
(Faculty of Graduate Studies and Research, University of Regina, 2014-04) Jin, Lei; Huang, Guo H.; Young, Stephanie; Dai, Liming; Yang, Boting; Song, Lianfa
With the increase and expansion of environmental requirements and dwindling of fossil fuel resources, current environmental and energy systems have aroused wide public concern. In this dissertation research, several optimization modeling methodologies have been developed for energy and environmental systems planning. They include: (a) a hybrid dynamic dual interval model (DDIP) for irrigation water allocation; (b) a robust interactive interval fully fuzzy model (RIIFFLP) for environmental systems planning; (c) a robust interval type-2 fuzzy set model (R-IT2FSLP) to manage irrigation water resources, (d) a robust inexact joint-optimal α cut interval type-2 fuzzy boundary model (RIJ-IT2FBLP) for planning of energy systems, and (e) a pseudo-optimal stochastic dual interval T2 fuzzy sets model (PD-IT2FSLP) for environmental pollutant control and energy systems planning. The DDIP has been developed by integrating dynamic programming (DP) with the dual interval technique into a general optimal framework. It was applied to a hypothetical case of irrigation water allocation in western Canada. The RIIFFLP method has been developed to deal with fully fuzzy uncertainties by using the fuzzy ranking method to find a balance between the necessity of constraints and the objective function of a linear interval fuzzy sets programming as a technique for optimal decision-making. The R-IT2FSLP method has been developed through integrating the concept of type-2 fuzzy sets with an interval fuzzy boundary model to achieve maximum system profits with limited environmental resources under uncertainties. The solutions obtained clearly show that the type-2 fuzzy sets methodology can provide significantly improved results that are more accurate by comparison to formal optimization methods. The RIJ-IT2FBLP model has been developed by combining the join-optimal α cut method, the interval RTSM solution method and the interval type-2 fuzzy sets boundary method. The developed model was applied to issues concerning long-term energy sources. The PD-IT2FSLP energy model has been developed to support energy system planning and environmental pollutant control under multiple uncertainties for Xiamen City in China. The solutions of the PD-IT2FSLP model will help energy authorities improve current energy consumption patterns and ascertain an optimal pattern for energy utilization in Xiamen City.
Open Access
Doubly Fed Induction Generator Control Using Artificial Neural Network for Wind Generation System
(Faculty of Graduate Studies and Research, University of Regina, 2021-08) Silva de Siqueira, Luanna Maria; Peng, Wei; Mayorga, Rene; Dai, Liming; Wu, Peng; Wang, Zhanle
Due to the electricity demand and environmental concerns, alternative clean forms of energy have been widely researched in recent years, in which wind energy is in evidence. To convert the mechanical energy generated by the wind turbines, the wind generation system needs generators. The doubly fed induction generator is the most commonly used due to its high energy transfer efficiency, reliability, and low maintenance cost. The control of DFIG parameters is crucial to the dynamic performance of the wind generation system. This thesis aims to develop an artificial neural network (ANN) controller for the doubly fed induction generator in wind generation system. It was proposed a data acquisition method using the system outcome with the conventional PI controller in order to train and test the ANN controller. The ANN controller was then designed and implemented in the system to control the machine speed, DC link voltage, and dq rotor and stator currents. In order to simulate the complete wind generation system, the models of DFIG, wind turbine, and converter were developed. The simulation results via Matlab Simulink indicate that it is possible to control the DFIG using an ANN controller. The results also show that the proposed ANN controller outperformed the conventional PI controller performances during the transient response, decreasing the overshoot for both machine speed and DC link voltage control. Outcomes found in this thesis combined with future works could potentially incentive the use of ANN for control purposes in wind generation systems. Furthermore, this research provides a guide on how to collect data for the training and testing of ANN controller for this kind of system.
Open Access
Dynamic Modeling and Vision-Based Mobile-Target Tracking in UAVs Using Wide FOV Cameras
(Faculty of Graduate Studies and Research, University of Regina, 2016-02) Majnoon, Mohsen; Mehrandezh, Mehran; Paranjape, Raman; Dai, Liming; Tontiwachwuthikul, Paitoon
Control of unmanned aerial vehicles is a very active topic in research with lots of applications ranging from civilian to military. To control a UAV, its attitude is often controlled using gyroscopes, but to control its position, inertial sensors together with GPS are often used. However, obtaining accurate current position is difficult using inertial sensors because of the integration drift. GPS on the other hand is not functional in indoor applications since it cannot connect to GPS satellites. Since vision has been proved to be an inexpensive and consistent source of relative position information, vision-based control is getting more popular in UAVs recently, but then again, using vision in outdoor applications is challenging as the target can move fast and out of the vision sensor field of view. So, in order to keep the target inside the field of view, two algorithms are being developed and tested via simulation in this research. Using pan/tilt/zoom cameras or multi camera systems, the target is guaranteed to stay in vision system field of view and hence, the vision based pose estimation can provide the control system with proper relative position. Two case studies - vision-based mobile-target tracking of a quadrotor using a multi-camera vision sensor and vision-based mobile-target tracking of a tilting rotor aircraft equipped with a zooming camera - are presented in this research to show the applicability of these methods in UAV control.
Open Access
Economic Order Quantity (EOQ) Measurement Using Intelligent Systems Techniques
(Faculty of Graduate Studies and Research, University of Regina, 2019-09) Moradizadeh, Sara; Mayorga, Rene; Dai, Liming; Peng, Wei; Azadbakht, Saman
Progressively, Intelligent Systems (IS) techniques have been used to reduce the uncertainty in complex problems. Because Intelligent Systems can be taught and predict the results, operations’ knowledge can be implemented into the systems. This Thesis is related to the application of Intelligent Systems to the solution of real-world problems, and it intends to estimate the Economic Order Quantity (EOQ) by using Intelligent Systems techniques. EOQ is the maximum number of inventories to be ordered at the time to minimize the company’s total costs of ordering, carrying, shortage and holding costs. There are some mathematical methods to calculate EOQ, but there are some disadvantages in using the formulas. Firstly, formulas cannot deal with vague and uncertain data, so if the inputs are not crisp or in linguistic terms, the formulas are not practical. Secondly, in some cases, due to some limitations (such as unpredictable markets, freshness of inventory in food and medicine industry), EOQ cannot be calculated by the formulas. In this situation, Intelligent Systems can help to determine the optimum EOQ. Using formulas, as done by conventional approaches, to calculate the optimum EOQ has some disadvantages; first, in some cases company’s demands/costs/expiry dates vary time to time and are not constant, so there is no constant number to include in the formulas. Moreover, in the case of vague or uncertain data, the formulas are not helpful and practical. Secondly, when EOQ is affected by other factors (such as freshness of inventory in perishable products, fragile/unpredictable markets), there is not a specific formula; therefore, using the formulas is not an option. Third, the conventional EOQ formula does not take into account the inflation rate. In this Thesis in order to reduce the uncertainty and enhance the efficiency, using Fuzzy Inference Systems for EOQ calculations is proposed. In this approach, the EOQ can be calculated in situations with vague data, uncertainty, no formulas, varied inputs, and fusion methods. Two methods of Fuzzy Inference Systems are used in this proposal in order to calculate the optimum EOQ: measuring EOQ by applying Mamdani Fuzzy Inference Systems; and measuring EOQ by applying Sugeno Fuzzy Inference Systems. The proposed nonconventional methodologies for EOQ are based on Intelligent Systems Techniques such as Fuzzy Inference Systems (FIS). The considered FIS has some advantages in EOQ calculations compared to EOQ conventional formulas. These advantages can be listed as: • They can deal with vague and uncertain data. • They can solve problems with inexplicit and incomplete data. • They can cover wide ranges of operating conditions. • They can be customized in linguistic terms. • They are user friendly, simpler and more flexible. This Thesis illustrates the methodologies in detail. The performance of these methods is examined, and the results are analyzed.
Open Access
Effects of Interfaces and Interactions between Multiphase Flow and Solid on Engineering Structures
(Faculty of Graduate Studies and Research, University of Regina, 2016-03) Wang, Xiaojie; Dai, Liming; Mehrandezh, Mehran; Aroonwilas, Adisorn; Volodin, Andrei; Peng, Qingjin
Phenomena involving interactions between liquids and solids are widely observed in natural and industrial applications. Interactions between different phases of fluids and solid structures have great importance in engineering applications such as aircraft and submarine designs, multiphase liquid flow analyses, aerodynamics, vehicle dynamics and in the fields of aeronautic, civil and mechanical engineering. The research in this dissertation focuses on numerical investigations of the effects of liquid-solid interactions on structures found in engineering systems and the nonlinear dynamic behaviors involved. The effects of liquid sloshing on a container mounted on a carrier are studied from an equivalent mechanical model of liquid sloshing in the container. The nonlinear mechanical model is presented and inviscid and viscous liquids are considered and compared for their effects on sloshing. The influence of gravitational acceleration on 3D nonlinear sloshing of the liquid in the carrier is studied in detail with a variety of system parameters. The motion and mobilization of multiphase fluid in porous media is analyzed, with a model in which oil slugs are trapped in an axisymmetric capillary tube saturated with water. Governing equations are derived for incompressible two-phase core-annular flow in the capillary model. Numerical solutions for capturing the evolution of the interface between oil and water are developed using a level set approach. The development of a water film surrounding the oil slug shows a significant effect on mobilizing the oil slug. The fluttering and oscillation of a panel structure is studied to investigate fluid-structure interactions and their effects on the structure. The interactions between fluid and structure are incorporated into the governing equations. A new approach based on the Periodicity Ratio method is developed in this study so the characteristics of a nonlinear system, subjected to non-periodic excitations, can be diagnosed. Vortex control of fluid flow over circular cylinders with detached plates are conducted numerically to develop a comprehensive understanding of the complex interactions a between fluid and structure, which is significant in aeronautic engineering. The uniform and linear shear intake flow are taken into consideration. The position and thickness of the detached plate are investigated. A thin plate separated from the cylinder plays an important role on the flow phenomenon in the vicinities of the cylinder and on the exertions applying on the cylinder subjected to the uniform and linear shear flow. Accuracy and reliability of the numerical calculations used in the engineering analyses are also investigated. The 4th-order Runge-Kutta method and a newly developed P-T method are studied and compared for their characteristics. Due to its inherent drawbacks found in the research, the Runge-Kutta method may cause information loss and lead to incorrect conclusions in comparison with the P-T method.
Open Access
Enhancement of Solubilization and Sorption Behaviors of Polycyclic Aromatic Hydrocarbons Through Involvement of Gemini Surfactants in Soil-Water Systems
(Faculty of Graduate Studies and Research, University of Regina, 2013-04) Wei, Jia; Huang, Guo H.; Chi, Guoxiang; Dai, Liming; Young, Stephanie; Xiao, Huining
Contamination of soil, sediment and water by polycyclic aromatic hydrocarbons (PAHs) has been recognized as a major, widespread, environmental waste concern. As a consequence, surfactant enhanced remediation (SER) has emerged as a promising technology for the removal of toxic PAHs. Gemini surfactants as a new generation of surfactants have structures and properties that are unique to the world of surfactants, such as greater efficiency in reducing surface tension and unusual aggregation morphologies in comparison with conventional surfactants. They have generated a growing interest owing to their superior performance in soil and water remediation applications. In this research, systematic studies have been physicochemically investigated in detail via tensiometric, conductometric and solubilization techniques to get insight into the micellar, interfacial and enhanced solubilization aspects of selected single and equimolar bi and ternary Gemini/Gemini and Gemini/conventional surfactant systems. A variety of mutual interaction parameters associated with the micellarization and solubilization process have been correlated through several theoretical treatments to understand the synergism and antagonism in solubilization capabilities of multi-component surfactant systems. Nonideality has been found due to a change in the microenvironment of the surfactant solution when various surfactants are mixed. The results have shown the solubilization power depends on the micellar and interfacial properties of the surfactant and their association with the hydrophilic/hydrophobic properties of solutes. Based on the solubilization analysis, the binding of select symmetric and dissymmetric Gemini surfactants with soil particles and their equilibrium distribution between solid and aqueous phases were evaluated. The adsorption isotherm is plotted and modeled to measure the surface coverage by surfactant molecules under a given condition to study the adsorption mechanism and, hence, determine the interfacial properties of modified solids. The sorption capacity of modified soils and natural soils and the overall partitioning of representative polycyclic aromatic hydrocarbons (PAHs) in a soil-water-surfactant system with a soil-sorbed Gemini surfactant and Gemini micelles are compared and related coefficients are developed. Major contributions coming from this research include: 1) A set of methodologies to evaluate and assist in the design of multi-component Gemini surfactant systems to enhance the solubility of polycyclic aromatic hydrocarbons (PAHs); 2) A clearer view of the effect of the structure of surfactants including the hydrophilic head group, hydrophobic chain length and spacer length, and the chemical nature of the solute on the micellar, interfacial and solubilization properties of surfactant systems; 3) Optimum Gemini surfactant mixtures for potential engineering application; 4) An explanation of the contaminant distribution pattern produced by the behavior of Gemini surfactant adsorption onto soils; 5) An investigation into the partitioning behavior of PAHs in a soil-water-Gemini surfactant and a development of the relative coefficients to produce an in-depth understanding of the mechanisms for surfactant enhanced remediation technology. The outputs of this study will be useful to understand and predict the solubilization and adsorption properties of Gemini surfactant systems and provide proof for exploring new surfactant systems for practical engineering applications.
Open Access
Evaluation of Liquid and Supercritical Carbon Dioxide Fracturing on Tight Sandstone Oil Reservoirs
(Faculty of Graduate Studies and Research, University of Regina, 2020-04) Hu, Haoran; Zeng, Fanhua; Azadbakht, Saman; Dai, Liming
Fracturing technology is an indispensable part in the development of low permeability reservoirs. In order to solve the problems of water consumption and formation damage, carbon dioxide (CO2) fracturing is treated as an alternative formation transformation and production enhancement technology for water-based fracturing. Several researches on fracturing mechanism and advantages of both liquid carbon dioxide (L-CO2) and supercritical carbon dioxide (Sc-CO2) mainly focused on the comparison and analysis of fracturing effects between different fracturing fluids, without evaluating the influence of fluid injection rate and core length for the effects of fracturing. Hence, as the important parameters in fracturing scheme design, it is necessary to study the effect of injection rate on L-CO2 fracturing and Sc-CO2 fracturing, as well as the effect of core length on L-CO2 fracturing. In this study, fracturing experiments with coreholder system, CT scanning, permeability and porosity tests are carried out to investigate and analysis breakdown pressure, permeability, porosity, 2D and 3D reconstruction images of each post-fractured tight sandstone cores. Since the micro-fractures formed by fracturing in the core are not easily detectable with limited experimental precision, the post-fractured core spontaneous imbibition experiments are introduced to reflect the generated fracture properties and the existence of secondary micro-cracks inside samples. Combined with one mathematical model of spontaneous imbibition oil recovery, a complete fracturing evaluation system under laboratory conditions is established on the basis of post-fractured core breakdown pressure, permeability and porosity, induced fracture morphology and propagation, spontaneous imbibition weight, imbibition potential and imbibition oil recovery, to evaluate fracturing performance in four major objectives: fracturing with different fracturing fluids, L-CO2 fracturing with different injection rate, Sc-CO2 fracturing with different injection rate, and L-CO2 fracturing with different core length. The results show that water-based fracturing tends to generate single and smooth fracture inside core, which has the highest breakdown pressure and lowest permeability. L-CO2 fracturing tends to form the short and narrow main fracture with transverse micro-cracks inside core. Sc-CO2 fracturing has a trend in creating the fracture network inside core, which has lowest breakdown pressure and highest permeability and calculated imbibition oil recovery. Besides, high-injection-rate L-CO2 fracturing path is specially long and straight with many longitudinal micro-fractures, resulting in post-fractured core with relatively high breakdown pressure, larger permeability, greater imbibition efficiency and oil recovery. In addition, with the increase of injection rate in Sc-CO2 fracturing, the fracture network structure created in the core becomes less distinct. Low-injection-rate Sc-CO2 fracturing has the best effect on core transformation because of post-fractured core with higher permeability, greater imbibition efficiency and oil recovery. Furthermore, L-CO2 fracturing is not ideal for transformation of overly long core sample.
Open Access
Experiment Study of Non-Equilibrium Phase Behavior and Effect of External Vibration on Heavy Oil Production
(Faculty of Graduate Studies and Research, University of Regina, 2022-03-30) Lu, Shixuan; Jia, Na; Dai, Liming; Gu, Yongan; Shirif, Ezeddin; Wu, Peng
In this thesis, two types of heavy oil experiments were explored to study the heavy oil non-equilibrium phase behavior and the influence of external vibration on heavy oil production performance. The first experiment was to use a Constant Composition Expansion and Compression (CCEC) tests to determine the pseudo-bubble point pressure at low (T = 15°C) and high (T = 75°C) temperature environment with three different volume change rates (“Fast Rate” 1.5 cm3/min; “Moderate Rate” 0.015 cm3/min; and “Slow Rate” 0.0003 cm3/min) and three different live heavy oil samples (15 mol% C2H6 + 85 mol% STO; 35 mol% C2H6 + 65 mol% STO; 55 mol% C2H6 + 45 mol% STO). The live oil samples were recombined with ethane and crude oil at the gas-oil ratio (GOR) of 8.63 cm3/cm3, 24.22 cm3/cm3; and 55.03 cm3/cm3, respectively. Then the live oil densities and viscosities of the homogenized mixing fluid were measured at different temperatures and pressures. The factors that affect the pseudo bubble point pressure of the live oil samples were examined, and it was found that high temperature, high gas concentration and low volume expansion rate resulted higher pseudo bubble point pressure. Also, the ethane-heavy oil samples were compared with the methane-heavy oil sample with the same GOR, and the latter had higher pseudo bubble point pressure than the former. The second experiment was to study the external vibration effect on heavy oil production. The external Vibration-Stimulated Gas Pressure Cycling (VS-GPC) processes with different vibration durations and frequencies were performed. The enhanced heavy oil recovery processes were compared in terms of the heavy oil recovery factor (RF), instantaneous gas production (iGP), production pressure (Pprod) and the production time of each cycle for all tests. The laboratory tests were conducted by using a cylindrical sandpacked physical model and the tests include one Gas Pressure Cycling (GPC) process, one GPC process with pre-vibration stimulation, three VS-GPC processes with 23.5-hour vibration at the same vibration frequencies, and three VS-GPC processes with 0.5-hour vibration at different vibration frequencies. The results demonstrated that the differences caused by vibration time (23.5 hrs vs. 0.5 hour) are marginal, and 2 Hz is the optimal frequency compared with 5 Hz and 20 Hz tests for this study. The heavy oil RFs for various VS-GPC process were ranked as follow: 2 Hz 0.5-hour VS-GPC > 5 Hz 23.5-hour VSGPC > 5 Hz 0.5-hour VS-GPC > 20 Hz 0.5-hour VS-GPC > pre-vibration GPC > GPC.
Open Access
Experimental and numerical investigations on wind characteristics and wind induced vibrations of bridge structures
(Faculty of Graduate Studies and Research, University of Regina, 2022-12) Xia, Dandan; Dai, Liming; Henni, Amr; Mehrandezh, Menrand; Morgan; Mobed, Nader; Li, Xianguo
As more and more flexible structures such as long span bridges and suspension bridges are built in the world, their increased flexibility can cause serious concerns for researchers and engineers. For such structures, wind load has become one of the most important dominant loads under consideration in the analysis and design of structures. Thus, accurate and reliable evaluations of the wind characteristics are critical, as the evaluations may provide a solid foundation for which the design of wind-resistant structures can be relied upon. Therefore, according to the importance and sensitivity of this subject in some special applications, the current research has been presented both analytically and experimentally, which may be utilized as guidance for researchers and engineers around the world in this field. The wind field measurement system used for this research acquires the high frequency wind speed data for the process of tropical cyclone and monsoon wind. Wind characteristics are studied systematically with wind data collected. Furthermore, the comparative study of stationary and non-stationary models, which is established with a self-adaptive procedure, is conducted. The established non-stationary model presents advantages for measuring the time related wind speed variations. Analytical results obtained in the research expose the difference between the traditional stationary and non-stationary models cannot be ignored, especially over a large time horizon. Moreover, in order to predict the wind speed with higher accuracy, a more accurate prediction method based on wavelet decomposition and chaotic diagnosis is also proposed. The wind speed prediction method considers the frequency domain characteristics of wind speed series for improving prediction accuracy. Wind speed data collected from the long term experiments and downloaded historical data are applied to verify the accuracy and reliability of the proposed prediction method. Wind induced vibration is another aspect which will affect the safety of the structures. As a typical and commonly seen type of wind induced vibration, vortex induced vibration (VIV) of bridges and the aerodynamic influences of the bridge attachments on the VIV are studied experimentally with a wind tunnel test. The effect of the attachments installed on the bridge deck such as crash barriers, wind barriers and traffic flows on VIV behaviors including lock-in wind speeds and vibration characteristics are systematically investigated. A new method by combing the unscented Kalman Filter with unknown input and simplification of Tylor series expression for studying the loads generated by vortex and VIV is proposed in the research. The governing equation developed is simplified by Taylor expression which can be applied for general bridge decks, unscented Kalman Filter with unknown input (UKF-UI) method is utilized to identify the self-excited and aerodynamic forces in VIV lock in regions. Instead of using fitted mathematical model, such a method can be directly applied on wind tunnel test data of general bridge deck types. The research findings are valuable for better analyzing and comprehending wind characteristics as well as interactions between wind and structures, and are expected to provide a practically sound guidance for designing wind-resistant structures especially flexible structures subject to wind exertion.
Open Access
Experimental Research on Multiphase Liquid Mobilization and Motion in Capillary and Micro Models Subjected to External Low Frequency Vibratory Excitations
(Faculty of Graduate Studies and Research, University of Regina, 2017-03) Zhang, Yihe; Dai, Liming; Mobed, Nader; Zeng, Fanhua; Henni, Amr; Mehrandezh, Mehran; Chen, Zengtao
The research of this dissertation experimentally investigates the impacts of external vibratory excitation on the mobilization and motion of multiphase liquid in capillary and microcell models, aiming for understanding the mechanism of oil-water mobilization and flow in pore structures subjected to external excitations. Experiments with capillary models are first conducted; in which both straight capillary and curved capillary models are employed as an analogue of the pore structures. The mobilization and motion of an oil slug trapped in the capillary models with capillary forces are studied in the research. The models considered are subjected to both external pressures created by water injection and vibratory excitations. The focuses of the experimental investigations are on the variation of the pressure drop across the capillary model, the oil slug travel distance in the model in a fixed time duration, and the flow phenomena during the period of mobilization and flow of the oil slug. It is found in the investigations, in comparing the situations of with and without external excitations, proper vibratory excitations may positively affect the mobilization and flow of the oil slug in the capillary models, in terms of reducing the external pressure needed for mobilizing the oil slug, stabilizing the flow of the oil slug and increasing the oil slug travel distance in a fixed duration. The joint effects of the external pressure and vibratory excitation on the mobilization and flow of the oil slug are measured and quantified in the research. The optimal conditions in terms of external pressure and vibration frequency and amplitude for promoting the oil slug mobilization and stable flow are also searched and determined via the experiments of the research. Two-dimensional micro model are more close to the pore structures of the reservoir in oil field. To study the motion of oil-water liquid in a two-dimensional manner, an etched glass micro model is designed and employed in the research to study the liquid mobilization and flow in a network pore structure. The intention of this study is to understand the mechanism of the external water pressure and vibratory excitation on oil recovery from liquid saturated porous media of a reservoir. Experiments without vibratory excitation are first conducted on the model and various phenomena are observed in the experiments, including the development of water film and water patches surrounding the oil droplets and oil patches, and the variations of the contact angles of the oil droplets. The experimental investigations with application of vibration excitation fall in two categories: oil displacement by applying vibration excitation after waterflooding and oil displacement by applying vibration excitation with waterflooding. The oil-displacing rate, oil-water distribution, and pressure drop are measured during the oil displacement. The fractional flow is calculated and analyzed. From the experimental results, it can be concluded that applying vibration excitation has positive effects on the oil displacement in terms of increasing the total oil-displacing rate in the micro model flow. The effect is much more noticeable when the oil-water ratio is high. Also, the efficiency of the oil recovery is found sensitive to the acceleration amplitude of the vibration excitation. By comparing the final oil-displacing rate, it is found that applying vibration excitation after waterflooding is more effective in comparing with that applying vibration excitation together with waterflooding.
Open Access
Generalized Unified Approach to Regression Models with Covariates Missing in Nonmonotone Patterns
(Faculty of Graduate Studies and Research, University of Regina, 2013-05) Liu, Meng; Zhao, Yang; Deng, Dianliang; Bae, Taehan; Dai, Liming; Chen, Bingshu E.
Complicated designs (eg. partially questionnaire design), which are often used in epidemiologic studies to reduce the cost of data collection while at the same time improving data quality, generate data with nonmonotone missing patterns. This thesis focuses on statistical inference for regression models with nonmonotone missing covariate data under some designs that generate nonmonotone missing data in covariates. Proposed methods in this scenario often depend on additional assumptions about covariates, for example, the covariates need to be categorical or follow a particular semiparametric joint distribution. This thesis describes a generalized unified estimation method for regression models with covariates missing in nonmonotone patterns which use a sequence of working regression models to extract information from incomplete observations. It can deal with both continuous and categorical variables. We consider both cross-sectional and longitudinal studies. The asymptotic theory and variance estimator for the generalized unified estimator are provided. Simulation studies in different settings are used to examine the proposed method. Finally we applied the generalized unified approach to the two real examples. One is a cross-sectional study, and the other is a longitudinal study.