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The effect of maps permutation on the global attractor of a periodic Beverton-Holt model
No full textConsider a p-periodic difference equation xn+1 = fn(xn) with a global attractor. How does a permutation [fσ(p−1), . . . , fσ(1), fσ(0)] of the maps affect the global attractor? In this paper, we limit this general question to the Beverton-Holt model with p-periodic harvesting. We fix a set of harvesting quotas and give ourselves the liberty to permute them. The total harvesting yield is unchanged by the permutation, but the population geometric-mean may fluctuate. We investigate this notion and characterize the cases in which a permutation of the harvesting quotas has no effect or tangible effect on the population geometric-mean. In particular, as long as persistence is assured, all permutations within the dihedral group give same population geometric-mean. Other permutations may change the population geometric-mean. A characterization theorem has been obtained based on block reflections in the harvesting quotas. Finally, we associate directed graphs to the various permutations, then give the complete characterization when the periodicity of the system is four or five
Face Flow: Constrained Optical Flow Framework for Faces
No full textA Master of Science thesis in Mechatronics Engineering by Muhannad Alkaddour entitled, “Face Flow: Constrained Optical Flow Framework for Faces”, submitted in May 2020. Thesis advisors are Dr. Usman Tariq and Dr. Abhinav Dhall. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).In computer vision, models and methods for facial expression recognition are continually in development. Several models aim to describe the highly complex structure of different faces, which in turn allows researchers to digitally process the faces based on these models for various tasks. With the rise of deep learning in 2012, many works have since used deep networks to learn facial expressions through both static and dynamic images. One main source of information for dynamic features are optical flow algorithms. These algorithms predict, from a sequence of frames, where each pixel moves from one frame to the next. The recent optical flow algorithms based on deep learning employ frameworks that are similar to those of deep convolutional autoencoders. Faces have a peculiar structure. Hence, it makes sense to think that this optical flow should be constrained based on the physically allowable movements of facial features. Combined with robust facial alignment algorithms, good optical flow estimation for faces can be used as features for emotion recognition in robots. These vision-based techniques can aid the robot to better interact with humans by incorporating affect recognition in the interaction, adding a psychological element to it. To carry out this investigation, we propose to construct a dataset with ground truth optical flow generated by observing the deformation of face keypoints and their neighborhoods between any two consecutive face images. The dataset is then used to train the FlowNetS deep network specialized in learning optical flow, aiming to infer the constrained optical flow from a given pair of face images. The network trained with the dataset is then compared to other setups in the testing phase, and the overall results show that using the generated data during training helps the network predict better optical flow representations on face sequences. The results of this thesis can be used as a precursor to obtain and make use of the dynamic features for unsupervised learning of facial expressions, which are important in applications such as human robot interaction, online learning, and electronic consumer relationship management.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR
Optimization of a Confined Jet Geometry to Improve Film Cooling Performance Using Response Surface Methodology (RSM)
No full textThis study investigates the interrelated parameters affecting heat transfer from a hot gas flowing on a flat plate while cool air is injected adjacent to the flat plate. The cool air forms an air blanket that shield the flat plate from the hot gas flow. The cool air is blown from a confined jet and is simulated using a two-dimensional numerical model under three variable parameters; namely, blowing ratio, jet angle and density ratio. The interrelations between these parameters are evaluated to properly understand their effects on heat transfer. The analyses are conducted using ANSYS-Fluent, and the performance of the air blanket is reported using local and average adiabatic film cooling effectiveness (AFCE). The interrelation between these parameters and the AFCE is established through a statistical method known as response surface methodology (RSM). The RSM model shows that the AFCE has a second order relation with the blowing ratio and a first order relation with both jet angle and density ratio. Also, it is found that the highest average AFCE is reached at an injection angle of 30 degree, a density ratio of 1.2 and a blowing ratio of 1.8
Optimal Planning of Distributed Generators and Shunt Capacitors in Isolated Microgrids With Nonlinear Loads
No full textThis article presents a comprehensive design procedure for isolated microgrids with a high penetration of nonlinear loads. The proposed microgrid planning approach simultaneously determines the sizes, locations and types of distributed generators (DGs) and shunt capacitor banks (CBs). The presence of nonlinear loads along with the capacitors of CBs or DGs' output filters may cause severe voltage distortions. To consider this issue, a harmonic power flow tool tailored for planning applications is developed that takes into account the specific features of isolated microgrids. Given the necessity of supply continuity for isolated microgrids after a contingency, the proposed planning approach takes into consideration the reliability to increase the probability of building successful islands. Unlike previous methods, the proposed approach does not rely merely on supply adequacy, and takes into account the fact that the voltage provision requirement can only be fulfilled through dispatchable DGs. The intermittent natures of loads and renewable DGs are modelled probabilistically. The effectiveness of the proposed planning approach has been validated using the PG&E 69-bus system, and the followings are observed: 1) the significance of applying suitable fundamental-power-flow and harmonic-power-flow algorithms for isolated microgrids, and 2) the possibility of avoiding a severe voltage distortion by utilizing an appropriate planning method and only small increase in the cost
Design and Assessment of an Innovative Thermal Management System for Electronic Cooling Using PCMs
No full textA Master of Science thesis in Mechanical Engineering by Yahya Abdulrahman Sheikh Mohammed entitled, “Design and Assessment of an Innovative Thermal Management System for Electronic Cooling Using PCMs”, submitted in July 2020. Thesis advisor is Mohamed Gadalla. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Thermal management of electronics is an important issue since the reliability of electronic components is greatly affected by the operating temperature. Electronics, such as laptops, are becoming more likely to overheat as their dimensions become smaller. Overheating an electronic device can cause problems such as a sudden shutdown, system freezing, and most importantly, it will affect its lifetime. To overcome this problem, a small vapor compression refrigeration (VCR) system integrated with Phase change materials (PCMs) is proposed. PCMs could be effective when electronic cooling systems such as heat sinks are considered. However, bio-based PCMs have poor thermal conductivity and therefore suffer from poor heat transfer characteristics. The diffusion of certain additives within the PCM has proven successful in the enhancement of heat transfer during the cooling process. Graphene Nanoplatelets (GNPs) presents itself as one such additive. This work experimentally investigates the cooling performance of the heat sink when GnPs and Graphite with various surfactants such as Sodium Dodecyl Sulfate (SDS), Sodium Dodecylbenzene Sulfonate (SDBS) and Sodium Stearoyl Lactylate (SSL) are added to the bio-based PCM. SSL NanoPCM provided a 345-sec delay compared to the Pure PCM, and the response time of PCM was improved be 51% when it was mixed with GnPs at 5% mass fraction. SDS surfactant indicated the highest increase in thermal conductivity when compared to others as it reported the highest increase of 368% when compared with the thermal conductivity of PurePCM. The main objective of this work is to design a new active cooling system to cope with increasing demand for powerful and high-performance electronics. The system is made of a compressor, an expansion device, a condenser, an evaporator, a fan, and a cold storage. The system is designed for laptop cooling with a cooling capacity of 100W and the dimension of the system is 38 × 30 × 15 cm. A comprehensive thermodynamic analysis was performed. While modelling the performance of the system, it is found that R134a has the best performance among the others. When the laptop cooler was used, the maximum temperature of the central processing unit (CPU) was found to be 67 °C, while it was 78 °C without using the cooler. Noticeably, using the cooler helped in reducing the temperature of CPU by 11 degrees (14.1%).College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Impact of IoT and Revenue-Sharing on Single and Two-Stage Pricing Strategies for Food Supply Chains
No full textA Master of Science thesis in Engineering Systems Management by Hafsa Saeed entitled, “Impact of IoT and Revenue-Sharing on Single and Two-Stage Pricing Strategies for Food Supply Chains”, submitted in December 2020. Thesis advisor is Dr. Mohamed Ben-Daya. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).With approximately one-third of the global production of food going to waste, immense research efforts are being directed towards identifying the underlying causes and potential solutions of this issue. Since a substantial amount of food waste can be attributed to the quality deterioration of perishable products within the food supply chains (FSC), therefore, one of the primary causes of this issue can be concluded to be inefficient FSCs. To combat this issue, this research examines the potential benefits of using Internet of Things (IoT) technology in the food supply chain within the framework of a two-echelon food supply chain comprising of a supplier and a retailer, and develops mathematical models to study the impact of real-time quality monitoring through IoT on single and two-stage pricing strategies. To this end, a literature review that lays the groundwork for the single and two-stage pricing models, developed in this research, is conducted. The model for each pricing strategy is developed within the decentralized, centralized, and revenue-sharing supply chain structure. The optimal points, used to analyze the individual and collective decisions of the supplier and the retailer, are derived for each model. The results of the numerical analysis indicate that the decision to employ IoT technology depends on the investment cost incurred and its correlation with the critical thresholds for the retailer, supplier, and the overall supply chain. These thresholds are determined through a combination of parameters that include the unit product cost, potential market size, quality deterioration rate, price and quality sensitivity factors, and the initial, organoleptic and critical quality of the perishable food products. Finally, the lower and upper bounds for the retailer’s revenue-sharing factor are ascertained, through a combination of the aforementioned parameters and the wholesale price, for an effective coordination that benefits both the supplier and the retailer.College of EngineeringMultidisciplinary ProgramsMaster of Science in Engineering Systems Management (MSESM
A discrete-time model with non-monotonic functional response and strong Allee effect in prey
No full textIn this paper, we investigate the impact of Allee effect on the stability of a discrete-time predator-prey model with a non-monotonic functional response. The proposed model supports the coexistence of two steady states, and the mathematical features of the model are analyzed based on local stability and bifurcation theory. By considering the Allee parameter as the bifurcation parameter, we provide sufficient conditions for the period-doubling and the Neimark-Sacker bifurcations. Also, sufficient conditions are given to show that increasing the magnitude of the Allee parameter within a certain domain plays a significant role in stabilizing the system
Characterizing the Acoustic Behavior of Hexagonal Periodic Cellular Cores
No full textA Master of Science thesis in Mechanical Engineering by Ammar Ahmed entitled, “Characterizing the Acoustic Behavior of Hexagonal Periodic Cellular Cores”, submitted in December 2020. Thesis advisor is Dr. Maen Alkhader and thesis co-advisor is Dr. Bassam Abu-Nabah. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Cellular solid cores are used in composite sandwich structures due to their high stiffness to weight ratio. However, owing to their porosity, they are inherently weak and are susceptible to damage due to improper loadings. As damaged cores can potentially lead to the failure of sandwich structures, core damage should be detected, preferably using nondestructive evaluation techniques. However, common nondestructive techniques, such as ultrasound, have limited effectiveness in inspecting cellular cores due to their dispersive properties. Since cellular cores are less dispersive at sub-ultrasound frequencies, inspecting them using sub-ultrasound frequencies has been introduced as a promising alternative to ultrasound inspection. However, this approach requires a priori knowledge of the acoustic characteristics in the inspected material, which is not available for most available cores. This work utilizes finite element computations to characterize the low frequency acoustic characteristics, namely phase velocity and dispersive properties, in commercial aluminum honeycombs made by bonding thin corrugated sheets. Results illustrate that the dispersive behavior and acoustic anisotropy of the studied honeycombs are more significant at higher porosities and higher frequencies. Moreover, results identify the frequencies below which honeycombs are least dispersive. To allow for realizing cores with tunable acoustic properties, the effect of admissible deformation modes, density, and geometric features on the phase velocities and dispersive properties is investigated. Accordingly, the acoustic behavior of honeycomb-based lattices that promote the two main admissible deformation modes in cellular solids, namely bending and stretching modes, is investigated. Results show that asymmetric waves in the bending dominated lattice are more direction dependent and less dispersive than in the stretching dominated lattice, whereas symmetric waves are generally independent of direction and dispersive in bending and stretching lattices. Results show that phase velocities of symmetric and asymmetric waves scale linearly with relative density in the bending dominated lattice and nonlinearly with relative density in the stretching dominated lattice; however, maximum phase velocities are higher in the stretching dominated lattice.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Strengthening of Shear Deficient Reinforced Concrete Beams using Anchored CFRP sheets
No full textA Master of Science thesis in Civil Engineering by Haya H. M. Mhanna entitled, “Strengthening of Shear Deficient Reinforced Concrete Beams Using Anchored CFRP Sheets”, submitted in May 2020. Thesis advisors are Dr. Rami Haweeleh and Dr. Jamal Abdalla. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Fiber-reinforced polymer (FRP) composite materials have been widely implemented to strengthen existing reinforced concrete (RC) structures in the past three decades. Studies have shown that externally bonding FRP materials to concrete substrate has proven to be effective in enhancing the shear capacity of RC beams. However, premature debonding of FRP laminates prevents the beam’s ability to utilize the laminates’ strength, and typically fail in a brittle mode. For this purpose, the current research aims to study the effect of anchoring CFRP laminates with CFRP splay anchors to strengthen RC T-beams in shear. The CFRP anchors are expected to delay or prevent debonding of the CFRP laminates, especially when the web of T-beams is shallow. There is still a gap in the available literature directed to the effect of FRP anchors on the strength and ductility of RC beams externally strengthened in shear with CFRP laminates. In addition, there are no design guidelines in the current codes of practice for strengthening with FRP anchors. Accordingly, a total of fifteen shear deficient T-beams were cast and externally strengthened with CFRP sheets in the form of U-Wraps and anchored with different configurations of CFRP splay anchor systems. The variables of the experimental program are anchor embedment depth, dowel diameter, insertion angle, and fan length. In addition, placing of the anchors before the U-wraps is investigated. The performance of the anchored U-wrapped specimens in terms of failure modes, load-deflection responses, shear strength, strain in CFRP laminates, and ductility is compared to that of unstrengthened and unanchored strengthened control specimens. Test results showed that CFRP anchors delayed debonding of the U-wraps, improved the shear strength of unanchored U-wraps by 14- 52%, and significantly enhanced the ductility of the beam specimens. It was concluded that bonding CFRP laminates by well-designed CFRP anchors highly utilized the strain attained in CFRP laminates. In addition, the FRP shear contribution is predicted using the ACI440.2R-17, CSA-S806.12(R2017), fib-14, and ISIS-M04 guidelines. Based on comparison with the experimental results, the ACI440.2R-17 and CSAS806.12(R2017) shear provisions provide reasonable predictions provided that the effective strain in CFRP laminates is limited to a value of 0.004.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Cyclic Sequential Removal of Alizarin Red S Dye and Cr(VI) Ions Using Wool as a Low-Cost Adsorbent
No full textAlizarin red S (ARS) removal from wastewater using sheep wool as adsorbent was investigated. The influence of contact time, pH, adsorbent dosage, initial ARS concentration and temperature was studied. Optimum values were: pH = 2.0, contact time = 90 min, adsorbent dosage = 8.0 g/L. Removal of ARS under these conditions was 93.2%. Adsorption data at 25.0 °C and 90 min contact time were fitted to the Freundlich and Langmuir isotherms. R2 values were 0.9943 and 0.9662, respectively. Raising the temperature to 50.0 °C had no effect on ARS removal. Free wool and wool loaded with ARS were characterized by Fourier Transform Infrared Spectroscopy (FTIR). ARS loaded wool was used as adsorbent for removal of Cr(VI) from industrial wastewater. ARS adsorbed on wool underwent oxidation, accompanied by a simultaneous reduction of Cr(VI) to Cr(III). The results hold promise for wool as adsorbent of organic pollutants from wastewater, in addition to substantial self-regeneration through reduction of toxic Cr(VI) to Cr(III). Sequential batch reactor studies involving three cycles showed no significant decline in removal efficiencies of both chromium and ARS