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Economic Allocation of Reliability Growth Testing Using Weibull Distributions
No full textReliability growth testing (RGT) has been widely used for assessing the reliability of complex systems in many industries such as automotive, aerospace, and oil and gas industry. The traditional common and practiced approach of RGT is to assess the initial reliability of the system by building and testing few prototypes for a period of time that extends from few months to years. Then, based on the initial reliability, initial testing time, and reliability target; the total testing time is determined using power law based models such as Duane and AMSAA/Crow models. In this paper, a new method is proposed to allocate RGT testing time for both
subsystems and system level in order to minimize system failure rate under limited cost and time resources. Unlike existing methods, intensity failure rate is assumed to be dynamic and modeled using Weibull distribution. Modeling using Weibull is more realistic and increases the applicability of the proposed method in real life applications. The proposed method is motivated by real life examples and its effectiveness is demonstrated by real-life examples
Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Get PDFA Master of Science thesis in Electrical Engineering by Yahya Bader Khawam entitled, "Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices", submitted in January 2016. Thesis advisor is Dr. Lutfi Albasha. Soft and hard copy available.This study presents an improved large signal model that can be used for High Electron Mobility Transistors (HEMTs) and Field Effect Transistors (FETs) using measurement-based behavioral modeling techniques. The steps for accurate large and small signal modeling for transistor are also discussed. The proposed DC model is based on the Fager model since it compensates between the number of model's parameters and accuracy. The objective is to increase the accuracy of the drain-source current model with respect to any change in gate-source or drain-source voltages. Also, the objective of this thesis work is to extend the improved DC model to account for soft breakdown and kink effect found in some variants of HEMT devices. A hybrid Newtons-Genetic algorithm is used in order to determine the unknown parameters in the developed model. In addition to accurate modeling of a transistor's DC characteristics, the complete large signal model is modeled using behavioral modeling techniques based on multi-bias s-parameter measurements. The targeted elements to be modeled in the complete large signal model are parasitic capacitances, parasitic inductances and parasitic resistances. The way that the complete model is performed is by using a hybrid multi-objective optimization technique (Non Dominated Sorting Genetic Algorithm II) and local minimum search (multi-variable Newton's method). Finally, the results of DC modeling and multi-bias s-parameters modeling are presented, and three device modeling recommendations are discussed.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Firm Internationalization and Corporate Social Responsibility
No full textUsing a large sample of 3,040 U.S. firms and 16,606 firm-year observations over the 1991–2010 period, we find strong evidence that firm internationalization is positively related to the firm’s corporate social responsibility (CSR) rating. This finding persists when we use alternative estimation methods, samples, and proxies for internationalization and when we address endogeneity concerns. We also provide evidence that the positive relation between internationalization and CSR rating holds for a large sample of firms from 44 countries. Finally, we offer novel evidence that firms with extensive foreign subsidiaries in countries with well-functioning political and legal institutions have better CSR ratings. Our findings shed light on the role of internationalization in influencing multinational firms’ CSR activities in the U.S. and around the worl
Efficient algortihms for constructing preset distinguishing sequences for nondeterministic finite state machines
Get PDFA Master of Science thesis in Computer Engineering by Abdul Rahim Haddad entitled, "Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines," submitted in June 2016. Thesis advisor is Dr. Khaled El-Fakih and thesis co-advisor is Dr. Gerassimos Barlas. Soft and hard copy available.Derivation of input sequences for distinguishing states of a finite state machine (FSM) specification is well studied in the context of FSM-based functional testing. We present three heuristics for the derivation of distinguishing sequences for nondeterministic FSM specifications. The first is based on a cost function that guides the derivation process, and the second is a genetic algorithm that evolves a population of individuals of possible solutions (or input sequences) using a fitness function and a crossover operator specifically tailored for the considered problem. The third heuristic is a mutation based algorithm that considers a candidate distinguishing sequence, and if the candidate is not a distinguishing sequence, then the algorithm tries to find a solution by appropriately mutating the candidate. Experiments are conducted to assess the performance of the proposed heuristics in addition to an existing algorithm, called exact algorithm, that derives distinguishing sequences of optimal length. Performance is assessed with respect to execution time, virtual memory consumption, and quality (length) of obtained sequences. Experiments are conducted using randomly generated machines with various numbers of states, inputs, outputs, and degrees of nondeterminism. Further, we assess the impact of varying the number of states, inputs, outputs, and degree of nondeterminism. Finally, in addition to the three proposed heuristics, we present a parallel multithreaded implementation of the exact algorithm using Open Multi-Processing. Experiments are conducted to assess the performance of the parallel implementation as compared to the sequential using both execution time speedup and efficiency.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Classification of Cognitive Workload Levels under Vague Visual Stimulation
No full textA Master of Science thesis in Computer Engineering by Rwan Adil Osman Mahmoud entitled, "Classification of Cognitive Workload Levels under Vague Visual Stimulation," submitted in May 2016. Thesis advisor is Dr. Tamer Shanableh and thesis co-advisor is Dr. Hasan Al Nashash. Soft and hard copy available.In most applications where humans are involved, it is important to augment the interaction between users and the components of these applications. One significant element is the cognitive state of the subjects involved. The cognitive state can be manipulated by the amount of cognitive workload allocated to the working memory. If the assigned cognitive workload is too low, the subject's cognition will be underutilized. In contrast, if the workload is more than the subject's capabilities, he or she will be mentally overloaded. Thus, there is a serious need to accurately assess and quantify cognitive workload levels.In this work, a method for separating four different cognitive workload levels is presented. We use an existing data set that contains EEG signals recorded from sixteen subjects while experiencing four different levels of cognitive workload. Some of these workload levels is due to the degradation of visual stimuli. The proposed solution integrates preprocessing of EEG signals, feature extraction based on discrete wavelet transform and statistical features, dimensionality reduction using stepwise regression and multiclass linear classification. Experimental results show that the average classification accuracy of the presented method is 93.4%. The effect of EEG channel selection on the classification accuracy is also investigated. The results show that channels included in the brain frontal lobes are important in cognitive workload classification. By utilizing only 23 channels, most of them are located in the frontal region; the proposed solution provides an average classification accuracy of 91%. It is shown that the proposed solution is more accurate and computationally less demanding when compared to the existing work.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Harvesting and stocking in discrete-time contest competition models with open problems and conjectures
No full textIn this survey, we present a class of first and second-order difference equations representing general form of discrete models arising from single-species with contest competition. Then, we consider various harvesting/stocking strategies and discuss their effect on stability, persistence and maximum sustainable yield. The main aim of this work is to give an account of recent results on the subject within a unified framework, then present some open questions and conjectures that deserve further investigation
INSPECT: A graphical user interface software package for IDARC-2D
No full textModern day Performance-Based Earthquake Engineering (PBEE) pivots about nonlinear analysis and its feasibility. IDARC-2D is a widely used and accepted software for nonlinear analysis; it possesses many attractive features and capabilities. However, it is operated from the command prompt in the DOS/Unix systems and requires elaborate text-based input files creation by the user. To complement and facilitate the use of IDARC-2D, a pre-processing GUI software package (INSPECT) is introduced herein. INSPECT is created in the C# environment and utilizes the .NET libraries and SQLite database. Extensive testing and verification demonstrated successful and high-fidelity re-creation of several existing IDARC-2D input files. Its design and built-in features aim at expediting, simplifying and assisting in the modeling process. Moreover, this practical aid enhances the reliability of the results and improves accuracy by reducing and/or eliminating many potential and common input mistakes. Such benefits would be appreciated by novice and veteran IDARC-2D users alike
Thermo-economic Optimization of Hybrid Combined Power Cycles Using Heliostat Field Collector
No full textA Master of Science thesis in Mechanical Engineering by Mohammad Saghafifar entitled, "Thermo-economic Optimization of Hybrid Combined Power Cycles Using Heliostat Field Collector," submitted in January 2016. Thesis advisor is Dr. Mohamed Gadalla. Soft and hard copy available.Electricity has an essential role in our daily life. However, with the ever increasing cost of fossil fuels and natural gas, power generation with higher efficiency and lower capital cost is in high demand. Nowadays, global warming and climate change have become vital issues prompting investigations into increasing the share of renewable sources of energy implementation in power generation. Solar energy is arguably the most favorable solution for a greener power generation technology. With solar technology's current level of maturity, solar energy cannot provide a significant contribution to the world's energy demand due to intermittency and storage issues. A possible solution to the aforementioned difficulties is power plant hybridization. In particular, concentrated solar power technologies are displaying significant potential for electricity production. The United Arab Emirates' hot, sunny climate is an indication of the great potential it possesses for hybrid and solar only power plant implementation. In this research work, the feasibility of a 50 MWe hybrid (solar and natural gas) combined cycle power plant with a topping gas turbine cycle and four different bottoming cycles are assessed. Power plant hybridization is accomplished by employing a solar tower collector (Heliostat field collector). Three rather unconventional bottoming cycle configurations have been chosen including gas turbine (air bottoming cycle), water injected gas turbine (humid air bottoming cycle), and the Maisotsenko cycle (Maisotsenko bottoming cycle). These three configurations along with the conventional combined cycle power plant (steam bottoming cycle) are optimized by conducting thermo-economic and transient analyses in MATLAB to identify the most economically justified plant configuration for the United Arab Emirates. Additionally, two different heliostat field layouts are taken into consideration including the radial-staggered and spiral layouts. Moreover, thermo-economic evaluation is accomplished by utilizing five different economic approaches, i.e. net present value, payback period, life cycle saving, Knopf objective function, and levelized cost of electricity.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Nonlinear Finite Element Analysis of Steel Shear Walls with Perforations
No full textA Master of Science thesis in Civil Engineering by Rana Ashour entitled, "Nonlinear Finite Element Analysis of Steel Shear Walls with Perforations," submitted in January 2016. Thesis advisor is Dr. Mohammad AlHamaydeh. Soft and hard copy available.The lateral load-resisting system of a building is an essential part of the structure and is critical for stability. Most reinforced concrete buildings around the world use reinforced concrete shear walls as their main lateral load-resisting system. Recently, Steel Plate Shear Walls (SPSWs) have become more widely accepted as an alternative to concrete shear walls especially for relatively taller buildings. Nevertheless, in
comparison to RC shear walls, there has not been as much research on steel shear walls in general, and specifically on steel shear walls with perforations. The main focus of this research is studying the impact of perforations on SPSW behavior. After presenting a summary of previous research, a Finite Element (FE) model is utilized to study the nonlinear behavior of perforated SPSWs. The model is created using the general-purpose commercial software package ABAQUS. Experimental results obtained from available literature are used to validate the model. The model is then used to carry out a deterministic sensitivity analysis in order to unveil the most influential parameters of the SPSW system. The investigated parameters are: (a) infill panel thickness, (b) beam size, (c) column size, (d) infill panel material yield strength, (e) frame material yield strength, (f) diameter of perforations and, (g) spacing of perforations. The input parameters are varied to two levels beyond the validated model control values. The effect of the studied parameters on the SPSW behavior is captured through monitoring key response indicators. The selected response indicators for SPSWs are: (a) yield strength, (b) yield displacement, (c) ultimate strength, (d) ultimate displacement, (e) initial stiffness, (f) secondary stiffness, (g) ductility and, (h) hysteretic energy in a full cycle of load reversal. The main effects of varying individual input parameters as well as input parameter interactions are explored. It is concluded that the parameter with the highest impact on all output parameters responses is infill panel thickness. Moreover, the most interactive parameters that are common to most output parameters are infill thickness with beam size and infill thickness with perforation diameter. Finally, the design guidelines produced can be used by designers to produce optimum designs and desired outcomes.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Al Ain Civic Center Revitalization Plan
No full textAn Urban Planning Research Workshop II (UPL 682) project by Doaa Habis, Emanuel Thomas, Maha Al Sayed, Manali Mondal, Mohamed Alamasi, Mohamed Al Ashram, and Rawan Y. Alghanim entitled, "Al Ain Civic Center Revitalisation Plan", submitted in Spring 2016. Project supervisor is Professor Rafael Pizarro