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Browsing by Author "Wasfy, Tamer"
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Item AI Based Modelling and Optimization of Turning Process(2012-08) Kulkarni, Ruturaj Jayant; El-Mounayri, Hazim; Anwar, Sohel; Wasfy, TamerIn this thesis, Artificial Neural Network (ANN) technique is used to model and simulate the Turning Process. Significant machining parameters (i.e. spindle speed, feed rate, and, depths of cut) and process parameters (surface roughness and cutting forces) are considered. It is shown that Multi-Layer Back Propagation Neural Network is capable to perform this particular task. Design of Experiments approach is used for efficient selection of values of parameters used during experiments to reduce cost and time for experiments. The Particle Swarm Optimization methodology is used for constrained optimization of machining parameters to minimize surface roughness as well as cutting forces. ANN and Particle Swarm Optimization, two computational intelligence techniques when combined together, provide efficient computational strategy for finding optimum solutions. The proposed method is capable of handling multiple parameter optimization problems for processes that have non-linear relationship between input and output parameters e.g. milling, drilling etc. In addition, this methodology provides reliable, fast and efficient tool that can provide suitable solution to many problems faced by manufacturing industry today.Item Assessment of STEM e-Learning in an Immersive Virtual Reality (VR) Environment(ASEE, 2018) Rogers, Christian B.; El-Mounayri, Hazim; Wasfy, Tamer; Satterwhite, Jesse; Computer and Information Science, School of ScienceThis paper shows the early research findings of utilizing a virtual reality environment as an educational tool for the operation of a computerized numerical control (CNC) milling machine. Based off of previous work, the Advanced Virtual Machining Lab (AVML), this project features an environment in which a virtual CNC machine is fully operable, designed to allow STEM students and training professionals to learn the use of the CNC machine without the need to be in a physical lab. Users operate in the virtual environment using an immersive virtual reality headset (i.e. Oculus Rift) and standard input devices (i.e. mouse and keyboard), both of which combined make for easy movement and realistic visuals. On-screen tutorials allow users to learn about what they need to do to operate the machine without the need for outside instruction. While designing and perfecting this environment has been the primary focus of this project thus far, the research goal is to test the ease of use and the pedagogical effectiveness of the immersive technology as it relates to education in STEM fields. Initial usability studies for this environment featured students from a CAD/CAM-Theory and Advanced Applications (ME 54600) course at a Midwestern urban institution. Results from the study were tabulated with a survey using a four-point Likert scale and several open-ended questions. Findings from the survey indicated that the majority of users found the environment realistic and easy to navigate, in addition to finding the immersive technology to be beneficial. Many also indicated that they felt comfortable navigating the environment without the need for additional assistance from the survey proctors. Full details on the usability study, including data and discussion, can be found in this paper. The general consensus from the study was that, while some features needed refinement, the immersive environment helped them learn about the operation of a CNC machine. An additional comparative study will be undertaken to evaluate pedagogical effectiveness.Item An Automated Grid-Based Robotic Alignment System for Pick and Place Applications(2013-12) Bearden, Lukas R.; Razban, Ali; Wasfy, Tamer; Li, Lingxi; Anwar, SohelThis thesis proposes an automated grid-based alignment system utilizing lasers and an array of light-detecting photodiodes. The intent is to create an inexpensive and scalable alignment system for pick-and-place robotic systems. The system utilizes the transformation matrix, geometry, and trigonometry to determine the movements to align the robot with a grid-based array of photodiodes. The alignment system consists of a sending unit utilizing lasers, a receiving module consisting of photodiodes, a data acquisition unit, a computer-based control system, and the robot being aligned. The control system computes the robot movements needed to position the lasers based on the laser positions detected by the photodiodes. A transformation matrix converts movements from the coordinate system of the grid formed by the photodiodes to the coordinate system of the robot. The photodiode grid can detect a single laser spot and move it to any part of the grid, or it can detect up to four laser spots and use their relative positions to determine rotational misalignment of the robot. Testing the alignment consists of detecting the position of a single laser at individual points in a distinct pattern on the grid array of photodiodes, and running the entire alignment process multiple times starting with different misalignment cases. The first test provides a measure of the position detection accuracy of the system, while the second test demonstrates the alignment accuracy and repeatability of the system. The system detects the position of a single laser or multiple lasers by using a method similar to a center-of-gravity calculation. The intensity of each photodiode is multiplied by the X-position of that photodiode. The summed result from each photodiode intensity and position product is divided by the summed value of all of the photodiode intensities to get the X-position of the laser. The same thing is done with the Y-values to get the Y-position of the laser. Results show that with this method the system can read a single laser position value with a resolution of 0.1mm, and with a maximum X-error of 2.9mm and Y-error of 2.0mm. It takes approximately 1.5 seconds to process the reading. The alignment procedure calculates the initial misalignment between the robot and the grid of photodiodes by moving the robot to two distinct points along the robot’s X-axis so that only one laser is over the grid. Using these two detected points, a movement trajectory is generated to move that laser to the X = 0, Y = 0 position on the grid. In the process, this moves the other three lasers over the grid, allowing the system to detect the positions of four lasers and uses the positions to determine the rotational and translational offset needed to align the lasers to the grid of photodiodes. This step is run in a feedback loop to update the adjustment until it is within a permissible error value. The desired result for the complete alignment is a robot manipulator positioning within ±0.5mm along the X and Y-axes. The system shows a maximum error of 0.2mm in the X-direction and 0.5mm in the Y-direction with a run-time of approximately 4 to 5 minutes per alignment. If the permissible error value of the final alignment is tripled the alignment time goes down to 1 to 1.5 minutes and the maximum error goes up to 1.4mm in both the X and Y-directions. The run time of the alignment decreases because the system runs fewer alignment iterations.Item Computational fluid dynamics analysis of the upper airway after rapid maxillary expansion: a case report(SpringerOpen, 2015-05-24) Ghoneima, Ahmed; AlBarakati, Sahar; Jiang, Feifei; Kula, Katherine; Wasfy, Tamer; Department of Orthodontics and Oral Facial Genetics, IU School of DentistryBACKGROUND: Assessment of the upper airway volume, morphology, and mechanics is of great importance for the orthodontic patient. We hypothesize that upper airway dimensions have significant effects on the dynamics of the airway flow and that both the dimensions and mechanics of the upper airway are greatly affected by orthodontic and orthopedic procedures such as rapid maxillary expansion (RME). The aim of the current study was to assess the effect of RME on the airway flow rate and pattern by comparing the fluid dynamics results of pre- and post-treatment finite element models. METHODS: Customized pre- and post-treatment computational fluid dynamics models of the patient's upper airway were built for comparison based on three-dimensional computed tomogram. The inhalation process was simulated using a constant volume flow rate for both models, and the wall was set to be rigid and stationary. Laminar and turbulent analyses were applied. RESULTS: Comparisons between before and after RME airway volume measurements showed that increases were only detected in nasal cavity volume, nasopharynx volume, and the most constricted area of the airway. Pressure, velocity, and turbulent kinetic energy decreased after dental expansion for laminar and turbulent flow. Turbulent flow shows relatively larger velocity and pressure than laminar flow. CONCLUSIONS: RME showed positive effects that may help understand the key reasons behind relieving the symptom of breathing disorders in this patient. Turbulence occurs at both nasal and oropharynx areas, and it showed relatively larger pressure and velocity compared to laminar flow.Item Coupled thermal-fluid analysis with flowpath-cavity interaction in a gas turbine engine(2013-12) Fitzpatrick, John Nathan; Wasfy, Tamer; Nalim, M. Razi; Yu, Huidan (Whitney); Anwar, SohelThis study seeks to improve the understanding of inlet conditions of a large rotor-stator cavity in a turbofan engine, often referred to as the drive cone cavity (DCC). The inlet flow is better understood through a higher fidelity computational fluid dynamics (CFD) modeling of the inlet to the cavity, and a coupled finite element (FE) thermal to CFD fluid analysis of the cavity in order to accurately predict engine component temperatures. Accurately predicting temperature distribution in the cavity is important because temperatures directly affect the material properties including Young's modulus, yield strength, fatigue strength, creep properties. All of these properties directly affect the life of critical engine components. In addition, temperatures cause thermal expansion which changes clearances and in turn affects engine efficiency. The DCC is fed from the last stage of the high pressure compressor. One of its primary functions is to purge the air over the rotor wall to prevent it from overheating. Aero-thermal conditions within the DCC cavity are particularly challenging to predict due to the complex air flow and high heat transfer in the rotating component. Thus, in order to accurately predict metal temperatures a two-way coupled CFD-FE analysis is needed. Historically, when the cavity airflow is modeled for engine design purposes, the inlet condition has been over-simplified for the CFD analysis which impacts the results, particularly in the region around the compressor disc rim. The inlet is typically simplified by circumferentially averaging the velocity field at the inlet to the cavity which removes the effect of pressure wakes from the upstream rotor blades. The way in which these non-axisymmetric flow characteristics affect metal temperatures is not well understood. In addition, a constant air temperature scaled from a previous analysis is used as the simplified cavity inlet air temperature. Therefore, the objectives of this study are: (a) model the DCC cavity with a more physically representative inlet condition while coupling the solid thermal analysis and compressible air flow analysis that includes the fluid velocity, pressure, and temperature fields; (b) run a coupled analysis whose boundary conditions come from computational models, rather than thermocouple data; (c) validate the model using available experimental data; and (d) based on the validation, determine if the model can be used to predict air inlet and metal temperatures for new engine geometries. Verification with experimental results showed that the coupled analysis with the 3D no-bolt CFD model with predictive boundary conditions, over-predicted the HP6 offtake temperature by 16k. The maximum error was an over-prediction of 50k while the average error was 17k. The predictive model with 3D bolts also predicted cavity temperatures with an average error of 17k. For the two CFD models with predicted boundary conditions, the case without bolts performed better than the case with bolts. This is due to the flow errors caused by placing stationary bolts in a rotating reference frame. Therefore it is recommended that this type of analysis only be attempted for drive cone cavities with no bolts or shielded bolts.Item Design optimization of heterogeneous microstructured materials(2014) Emami, Anahita; Tovar, Andrés; Zhu, Likun; Wasfy, Tamer; Chen, JieOur ability to engineer materials is limited by our capacity to tailor the material’s microstructure morphology and predict resulting properties. The insufficient knowledge on microstructure-property relationship is due to complexity and randomness in all materials at different scales. The objective of this research is to establish a design optimization methodology for microstructured materials. The material design problem is stated as finding the optimum microstructure to maximize the desired performance satisfying material processing constrains. This problem has been solved in this thesis by means of numerical techniques through four main steps: microstructure characterization, model reconstruction, property evaluation, and optimization. Two methods of microstructure characterizations have been investigated along with the advantages and disadvantages of each method. The first microstructure characterization method is a statistical method which utilizes correlation functions to extract the microstructural information. Algorithms for calculating these correlations functions have been developed and optimized based on their computational cost using MATLAB software. The second microstructure characterization method is physical characterization which works based on evaluation of physical features in microstructured domain. These features have been measured by means of MATLAB codes. Three model reconstruction techniques are proposed based on these characterization methods and employed to generate material models for further evaluation. The first reconstructing algorithm uses statistical functions to reconstruct the statistical equivalent model through simulating annealing optimization method. The second algorithm uses cellular automaton concepts to simulate the grain growth utilizing physical descriptors, and the third one generates elliptical inclusions in a material matrix using physical characteristic of microstructure. The finite element method is used to analysis the mechanical behavior of material models. Several material samples with different microstructural characteristics have been generated to model the micro-scale design domain of AZ31 magnesium alloy and magnesium matrix composite with silicon carbide fibers. Then, surrogate models have been created based on these samples to approximate the entire design domain and demonstrate the sensitivity of the desired mechanical property to two independent microstructural features. Finally, the optimum microstructure characteristics of material samples for fracture strength maximization have been obtained.Item Design, analysis, and simulation of a humanoid robotic arm applied to catching(2014) Yesmunt, Garrett Scot; Wasfy, Tamer; El-Mounayri, Hazim; Razban, Ali; Chen, JieThere have been many endeavors to design humanoid robots that have human characteristics such as dexterity, autonomy and intelligence. Humanoid robots are intended to cooperate with humans and perform useful work that humans can perform. The main advantage of humanoid robots over other machines is that they are flexible and multi-purpose. In this thesis, a human-like robotic arm is designed and used in a task which is typically performed by humans, namely, catching a ball. The robotic arm was designed to closely resemble a human arm, based on anthropometric studies. A rigid multibody dynamics software was used to create a virtual model of the robotic arm, perform experiments, and collect data. The inverse kinematics of the robotic arm was solved using a Newton-Raphson numerical method with a numerically calculated Jacobian. The system was validated by testing its ability to find a kinematic solution for the catch position and successfully catch the ball within the robot's workspace. The tests were conducted by throwing the ball such that its path intersects different target points within the robot's workspace. The method used for determining the catch location consists of finding the intersection of the ball's trajectory with a virtual catch plane. The hand orientation was set so that the normal vector to the palm of the hand is parallel to the trajectory of the ball at the intersection point and a vector perpendicular to this normal vector remains in a constant orientation during the catch. It was found that this catch orientation approach was reliable within a 0.35 x 0.4 meter window in the robot's workspace. For all tests within this window, the robotic arm successfully caught and dropped the ball in a bin. Also, for the tests within this window, the maximum position and orientation (Euler angle) tracking errors were 13.6 mm and 4.3 degrees, respectively. The average position and orientation tracking errors were 3.5 mm and 0.3 degrees, respectively. The work presented in this study can be applied to humanoid robots in industrial assembly lines and hazardous environment recovery tasks, amongst other applications.Item Electrochemical model based condition monitoring of a Li-ion battery using fuzzy logic(2014) Shimoga Muddappa, Vinay Kumar; Anwar, Sohel; Wasfy, Tamer; Li, LingxiThere is a strong urge for advanced diagnosis method, especially in high power battery packs and high energy density cell design applications, such as electric vehicle (EV) and hybrid electric vehicle segment, due to safety concerns. Accurate and robust diagnosis methods are required in order to optimize battery charge utilization and improve EV range. Battery faults cause significant model parameter variation affecting battery internal states and output. This work is focused on developing diagnosis method to reliably detect various faults inside lithium-ion cell using electrochemical model based observer and fuzzy logic algorithm, which is implementable in real-time. The internal states and outputs from battery plant model were compared against those from the electrochemical model based observer to generate the residuals. These residuals and states were further used in a fuzzy logic based residual evaluation algorithm in order to detect the battery faults. Simulation results show that the proposed methodology is able to detect various fault types including overcharge, over-discharge and aged battery quickly and reliably, thus providing an effective and accurate way of diagnosing li-ion battery faults.Item Experimental Validation of Non-cohesive Soil Using Discrete Element Method(2018-12) Roy, Ayan; Wasfy, Tamer; Tovar, Andres; El-Mounyari, HanzimIn this thesis, an explicit time integration code which integrates multibody dynamics (MBD) and the discrete element method (DEM) is validated using three previously published steady-state physical experiments for non-cohesive sand-type material, namely: shear-cell for measuring shear stress versus normal stress; penetroplate pressure-sinkage test; and wheel drawbar pull-torque-slip test. The test results are used to calibrate the material properties of the DEM soft soil model and validate the coupled MBD-DEM code. All three tests are important because each test measures specific mechanical characteristics of the soil under various loading conditions. Shear strength of the soil as a function of normal load help to understand shearing of the soil under a vehicle wheel contact patch causing loss of traction. Penetroplate pressure-sinkage test is used to calibrate and validate friction and shear strength characteristics of the soil. Finally the rigid wheel-soil interaction test is used to predict drawbar pull force and wheel torque vs. slip percentage and normal stress for a rigid wheel. Wheel-Soil interaction test is important because it plays the role of ultimate validation of the soil model tuned in the previous two experiments and also shows how the soil model behaves in vehicle mobility applications. All the aforementioned tests were modeled in the multibody dynamics software using rigid bodies and various joints and actuators. The sand-type material is modeled using discrete cubical particles. A penalty technique is used to impose normal contact constraints (including particle-particle and particle-wall contact). An asperity-based friction model is used to model friction. A Cartesian Eulerian grid contact search algorithm is used to allow fast contact detection between particles. A recursive bounding box contact search algorithm enabled fast contact detection between the particles and polygonal body surfaces (such as walls, penetrometer, and wheel). The governing equations of motion are solved along with contact constraint equations using a time-accurate explicit solution procedure. The results show very good agreement between the simulation and the experimental measurements. The model is then demonstrated in a full-scale application of high-speed off-road vehicle mobility on the sand-type soil.Item High-fidelity modeling of a backhoe digging operation using an explicit multibody dynamics finite element code with integrated discrete element method(2013-11-06) Ahmadi Ghoohaki, Shahriar; Wasfy, Tamer; El-Mounayri, Hazim; Zhu, Likun; Chen, JieIn this thesis, a high- fidelity multibody dynamics model of a backhoe for simulating the digging operation is developed using the DIS (Dynamic Interactions Simulator)multibody dynamics software. Sand is used as a sample digging material to illustrate the model. The backhoe components (such as frame, manipulators links,track segments, wheels and sprockets) are modeled as rigid bodies. The geometry of the major moving components of the backhoe is created using the Pro/E solid modeling software. The components of the backhoe are imported to DIS and connected using joints (revolute, cylindrical and prismatic joints). Rotary and linear actuators along with PD (Proportional-Derivative) controllers are used to move and steer the backhoe and to move the backhoes manipulator in the desired trajectory. Sand is modeled using cubic shaped particles that can come into contact with each other, the backhoes bucket and ground. A cubical sand particle contact surface is modeled using eight spheres that are rigidly glued to each other to form a cubical shaped particle, The backhoe and ground surfaces are modeled as polygonal surfaces. A penalty technique is used to impose both joint and normal contact constraints (including track-wheels, track-terrain, bucket-particles and particles-particles contact). An asperity-based friction model is used to model joint and contact friction. A Cartesian Eulerian grid contact search algorithm is used to allow fast contact detection between particles. A recursive bounding box contact search algorithm is used to allow fast contact detection for polygonal contact surfaces and is used to detect contact between: track and ground; track and wheels; bucket and particles; and ground and particles. The governing equations of motion are solved along with joint/constraint equations using a time-accurate explicit solution procedure. The sand model is validated using a conical hopper sand flow experiment in which the sand flow rate during discharge and the angle of repose of the resulting sand pile are experimentally measured. The results of the conical hopper simulation are compared with previously published experimental results. Parameter studies are performed using the sand model to study the e ffects of the particle size and the orifi ces diameter of the hopper on the sand pile angle of repose and sand flow rate. The sand model is integrated with the backhoe model to simulate a typical digging operation. The model is used to predict the manipulators actuator forces needed to dig through a pile of sand. Integrating the sand model and backhoe model can help improving the performance of construction equipment by predicting, for various vehicle design alternatives: the actuator and joint forces, and the vehicle stability during digging.