Mechanical and Mechatronics Engineering

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This is the collection for the University of Waterloo's Department of Mechanical and Mechatronics Engineering.

Research outputs are organized by type (eg. Master Thesis, Article, Conference Paper).

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3D Ground Truth Generation Using Pre-Trained Deep Neural Networks
(University of Waterloo, 2019-05-24) Lee, Jungwook
Training 3D object detectors on publicly available data has been limited to small datasets due to the large amount of effort required to generate annotations. The difficulty of labeling in 3D using 2.5D sensors, such as LIDAR, is attributed to the high spatial reasoning skills required to deal with occlusion and partial viewpoints. Additionally, the current methods to label 3D objects are cognitively demanding due to frequent task switching. Reducing both task complexity and the amount of task switching done by annotators is key to reducing the effort and time required to generate 3D bounding box annotations. We therefore seek to reduce the burden on the annotators by leveraging existing 3D object detectors using deep neural networks. This work introduces a novel ground truth generation method that combines human supervision with pre-trained neural networks to generate per-instance 3D point cloud seg- mentation, 3D bounding boxes, and class annotations. The annotators provide object anchor clicks which behave as a seed to generate instance segmentation results in 3D. The points belonging to each instance are then used to regress object centroids, bounding box dimensions, and object orientation. The deep neural network model used to generate the segmentation masks and bounding box parameters is based on the PointNet architecture. We develop our approach with reliance on the KITTI dataset to analyze the quality of the generated ground truth. The neural network model is trained on KITTI training split and the 3D bounding box outputs are generated using annotation clicks collected from the validation split. The validation split of KITTI detection dataset contains 3712 frames of pointcloud and image scenes and it took 16.35 hours to label with the following method. Based on these results, our approach is 19 times faster than the latest published 3D object annotation scheme. Additionally, it is found that the annotators spent less time per object as the number of objects in the scenes increase, making it a very efficient for multi-object labeling. Furthermore, the quality of the generated 3D bounding boxes, using the labeling method, is compared against the KITTI ground truth. It is shown that the model performs on par with the current state-of-the-art 3D detectors and the labeling procedure does not negatively impact the output quality of the bounding boxes. Lastly, the proposed scheme is applied to previously unseen data from the Autonomoose self-driving vehicle to demonstrate generalization capabilities of the network.
3D Motion Planning using Kinodynamically Feasible Motion Primitives in Unknown Environments
(University of Waterloo, 2011-09-01T14:31:18Z) Chen, Peiyi
Autonomous vehicles are a great asset to society by helping perform many dangerous or tedious tasks. They have already been successfully employed for many practical applications, such as search and rescue, automated surveillance, exploration and mapping, sample collection, and remote inspection. In order to perform most tasks autonomously, the vehicle must be able to safely and efficiently navigate through its environment. The algorithms and techniques that allow an autonomous vehicle to find traversable paths to its destination defines the set of problems in robotics known as motion planning. This thesis presents a new motion planner that is capable of finding collision-free paths through an unknown environment while satisfying the kinodynamic constraints of the vehicle. This is done using a two step process. In the first step, a collision-free path is generated using a modified Probabilistic Roadmap (PRM) based planner by assuming unexplored areas are obstacle-free. As obstacles are detected, the planner will replan the path as necessary to ensure that it remains collision-free. In complex environments, it is often necessary to increase the size of the PRM graph during the replanning step so that the graph remains connected. However, this causes the algorithm to slow down significantly over time. To mitigate these issues, the novel local sampling and PRM regeneration techniques are used to increase the computational efficiency of the replanning step. The local sampling technique biases the search towards the neighborhood of the obstacle blocking the path. This encourages the planner to generate small detours around the obstacle instead of rerouting the whole path. The PRM regeneration technique is used to remove all non-critical nodes from the PRM graph. This is used to bound the size of the PRM graph so that it does not grow increasingly large over time. In the second step, the collision-free path is transformed into a series of kinodynamically feasible motion primitives using two novel algorithms: the heuristic re-sampling algorithm and the transformation algorithm. The heuristic re-sampling algorithm is a greedy heuristic algorithm that increases the clearance around the path while removing redundant segments. This algorithm can be applied to any piece-wise linear path, and is guaranteed to produce a solution that is at least as good as the initial path. The transformation algorithm is a method to convert a path into a series of kinodynamically feasible motion primitives. It is extremely efficient computationally, and can be applied to any piece-wise linear path. To achieve good computational performance with PRM based planners, it is necessary to use sampling strategies that can efficiently form connected graphs through narrow and complex regions of the configuration space. Many proposed sampling methods attempt to bias the sample density in favor of these difficult to connect areas. However, these methods do not distinguish between samples that lie inside narrow passages and those that lie along convex borders. The orthogonal bridge test is a novel sampling technique that can identify and reject samples that lie along convex borders. This allows connected PRM graphs to be constructed with fewer nodes, which leads to less collision checking and reduced runtimes. The presented algorithms are experimentally verified using an AR.Drone quadrotor unmanned aerial vehicle (UAV) and a custom built skid-steer unmanned ground vehicle (UGV). Using a simple kinematic model and a basic position controller, the AR.Drone is able to traverse a series of motion primitives with less than 0.3 m of crosstrack error. The skid-steer UGV is able to navigate through unknown environments filled with obstacles to reach a desired destination. Furthermore, the observed runtimes of the proposed motion planner suggest that it is fully capable of computing solution paths online. This is an important result, because online computation is necessary for efficient autonomous operations and it can not be achieved with many existing kinodynamic motion planners.
3D Shape Reconstruction of Knee Bones from Low Radiation X-ray Images Using Deep Learning
(University of Waterloo, 2021-06-02) Hampali, Shamanth
Understanding the bone kinematics of the human knee during dynamic motions is necessary to evaluate the pathological conditions, design knee prosthesis, orthosis and surgical treatments such as knee arthroplasty. Also, knee bone kinematics is essential to assess the biofidelity of the computational models. Kinematics of the human knee has been reported in the literature either using in vitro or in vivo methodologies. In vivo methodology is widely preferred due to biomechanical accuracies. However, it is challenging to obtain the kinematic data in vivo due to limitations in existing methods. One of the several existing methods used in such application is using X-ray fluoroscopy imaging, which allows for the non-invasive quantification of bone kinematics. In the fluoroscopy imaging method, due to procedural simplicity and low radiation exposure, single-plane fluoroscopy (SF) is the preferred tool to study the in vivo kinematics of the knee joint. Evaluation of the three-dimensional (3D) kinematics from the SF imagery is possible only if prior knowledge of the shape of the knee bones is available. The standard technique for acquiring the knee shape is to either segment Magnetic Resonance (MR) images, which is expensive to procure, or Computed Tomography (CT) images, which exposes the subjects to a heavy dose of ionizing radiation. Additionally, both the segmentation procedures are time-consuming and labour-intensive. An alternative technique that is rarely used is to reconstruct the knee shape from the SF images. It is less expensive than MR imaging, exposes the subjects to relatively lower radiation than CT imaging, and since the kinematic study and the shape reconstruction could be carried out using the same device, it could save a considerable amount of time for the researchers and the subjects. However, due to low exposure levels, SF images are often characterized by a low signal-to-noise ratio, making it difficult to extract the required information to reconstruct the shape accurately. In comparison to conventional X-ray images, SF images are of lower quality and have less detail. Additionally, existing methods for reconstructing the shape of the knee remain generally inconvenient since they need a highly controlled system: images must be captured from a calibrated device, care must be taken while positioning the subject's knee in the X-ray field to ensure image consistency, and user intervention and expert knowledge is required for 3D reconstruction. In an attempt to simplify the existing process, this thesis proposes a new methodology to reconstruct the 3D shape of the knee bones from multiple uncalibrated SF images using deep learning. During the image acquisition using the SF, the subjects in this approach can freely rotate their leg (in a fully extended, knee-locked position), resulting in several images captured in arbitrary poses. Relevant features are extracted from these images using a novel feature extraction technique before feeding it to a custom-built Convolutional Neural Network (CNN). The network, without further optimization, directly outputs a meshed 3D surface model of the subject's knee joint. The whole procedure could be completed in a few minutes. The robust feature extraction technique can effectively extract relevant information from a range of image qualities. When tested on eight unseen sets of SF images with known true geometry, the network reconstructed knee shape models with a shape error (RMSE) of 1.91± 0.30 mm for the femur, 2.3± 0.36 mm for the tibia and 3.3± 0.53 mm for the patella. The error was calculated after rigidly aligning (scale, rotation, and translation) each of the reconstructed shape models with the corresponding known true geometry (obtained through MRI segmentation). Based on a previous study that examined the influence of reconstructed shape accuracy on the precision of the evaluation of tibiofemoral kinematics, the shape accuracy of the proposed methodology might be adequate to precisely track the bone kinematics, although further investigation is required.
A New Tightly-Coupled Dual-VIO for a Mobile Manipulator with Dynamic Locomotion
(University of Waterloo, 2024-09-12) Xu, Jianxiang
This thesis presents a novel approach to address the challenges encountered by a mobile manipulator engaged in dynamic locomotion within cluttered environments. The proposed technique involves the use of a dual monocular visual-inertial odometry (dual-VIO) strategy, which integrates two independent monocular VIO modules, one at the mobile base and the other at the end eﬀector (EE). These modules are intricately coupled at the low level of the factor graph to provide a robust solution. The approach leverages arm kinematics to treat each monocular VIO as a positional anchor in relation to the other, thereby introducing a soft geometric constraint during VIO pose optimization. This mechanism eﬀectively stabilizes both estimators, mitigating potential instability during highly dynamic locomotions. The performance of the proposed approach has been rigorously evaluated through extensive experimental testing, directly comparing it to the concurrent operation of independent dual Monocular VINS (VINS-Mono). The envisaged impact extends beyond the speciﬁc application, as the approach may lay the groundwork for multi-VIO fusion and enhanced system redundancy within the realm of Active-SLAM (A-SLAM).
Absorption of Nitric Oxide from Flue Gas Using Ammoniacal Cobalt(II) Solutions
(University of Waterloo, 2013-01-24T15:45:01Z) Yu, Hesheng
Air emissions from the combustion of fossil fuel, including carbon dioxide, sulfur dioxide, nitrogen dioxide and nitric oxide, have caused severe health and environmental problems. The post-combustion wet scrubbing has been employed for control of carbon dioxide and sulfur dioxide emissions. However, it is restricted by the sparingly water soluble nitric oxide, which accounts for 90-95% of nitrogen oxides. It is desirable and cost-effective to remove nitric oxide from flue gas by existing wet scrubbers for reduced capital costs and foot prints. In this research, absorption of nitric oxide from simulated flue gas using three different absorbents was first conducted in a bubble column system at room temperature and atmospheric pressure. Through performance comparison, ammoniacal cobalt(II) solutions were chosen as the optimum absorbent for nitric oxide absorption. Then the effects of fresh absorbent composition, pH value and temperature on nitric oxide absorption were investigated. Experimental results showed that the best initial NO removal efficiency of 96.45% was measured at the inlet flow rate of 500 mL·min-1; the room temperature of 292.2 K; the pH value of 10.50; and the concentrations of cobalt(II) solution, NO and O2 of 0.06 mol·L-1, 500 ppmv and 5.0%, respectively. For in-depth understanding of NO absorption into ammoniacal cobalt(II) complexes, equilibrium constants of reactions between nitric oxide and penta- and haxa-amminecobalt(II) solutions, respectively were determined using a bubble column reactor, in which the operation was performed continuously with respect to gas phase and batch-wise with respect to liquid phase. The experiments were conducted at temperatures from 298.2 to 310.2 K and pH from 9.06 to 9.37, all under atmospheric pressure. All experimental data fitted well to the following equations: K_NO^5=1.90×10^7 exp(3598.5/T) and K_NO^6=3.56×10^11 exp(1476.4/T), which give the enthalpy of reactions between NO and penta- and hexa-amminecobalt (II) nitrates as ∆H^5=-29.92 kJ·mol^(-1) and ∆H^6=-12.27 kJ·mol^(-1). In kinetic study, a number of experiments were conducted in a home-made double-stirred reactor at temperatures of 298.2 and 303.2 K and pH from 8.50 to 9.87 under atmospheric pressure. The reaction rate constants were calculated with the use of enhancement factor derived for gas absorption accompanied by parallel chemical reactions. The reaction between NO and pentaaminecobalt(II) was first order with respect to NO and pentaamminecobalt(II) ion, respectively. Similarly, the reaction between NO and hexaaminecobalt(II) was also first order with respect to NO and hexaamminecobalt(II) ion, respectively. The forward reaction rate constants of these two reactions were 6.43×10^6 and 1.00×10^7 L·mol-1·s-1, respectively at 298.2 K, and increased to 7.57×106 and 1.12×107 L∙mol-1∙s-1, respectively at 303.2 K. Furthermore, regeneration of used absorbent was attempted but fails. None of the additives tested herein including potassium iodide (KI), sodium persulphate (Na2S5O8) and activated carbon (AC) showed capability of regeneration at room temperature and atmospheric pressure. In addition, the effect of oxygen was investigated. With ammoniacal cobalt(II) compounds a positive effect of oxygen on NO absorption was observed. Calculated NO amount absorbed into the aqueous solution showed that with the oxygen the absorption reaction could be considered as irreversible. This fact was probably the reason for the failure of regeneration of the tested reagents. Last but not least, volumetric liquid-phase mass transfer coefficient, kLa, in some popular industrial absorbers including bubble column (BC), conventional stirred tank reactor (CSTR) and gas-inducing agitated tank (GIAT) were determined by modeling removal of oxygen from water. The experimental results could be well interpreted by mathematical models with 90% of deviations less than ±10 %.
Acausal Powertrain Modelling with Application to Model-based Powertrain Control
(University of Waterloo, 2014-02-21) Adibi Asl, Hadi
The automotive industry has long been searching for efficient ways to improve vehicle performance such as drivability, fuel consumption, and emissions. Researchers in the automotive industry have tried to develop methods to improve fuel consumption and reduce the emission gases of a vehicle, while satisfying drivability and ride comfort issues. Today, by developing computer/software technologies, automotive manufacturers are moving more and more towards modelling a real component (prototype) in a software domain (virtual prototype). For instance, modelling the components of a vehicle's powertrain (driveline) in the software domain helps the designers to iterate the model for different operating conditions and scenarios to obtain better performance without any cost of making a real prototype. The objective of this research is to develop and validate physics-based powertrain models with sufficient fidelity to be useful to the automotive industry for rapid prototyping. Developing a physics-based powertrain model that can accurately simulate real phenomenon in the powertrain components is of great importance. For instance, a high-fidelity simulation of the combustion phenomenon in the internal combustion (IC) engine with detailed physical and chemical reactions can be used as a virtual prototype to estimate physical prototype characteristics in a shorter time than it would take to build a physical prototype. Therefore, the powertrain design can be explored and validated virtually in the software domain to reduce the cost and time of product development. The main focus of this thesis is on development of an internal combustion engine model, four-cylinder spark ignition engine, and a hydrodynamic torque converter model. Then, the models are integrated along with the rest of a powertrain's components (e.g. vehicle longitudinal dynamics model) through acausal connections, which represents a more feasible physics-based powertrain model for model-based control design. The powertrain model can be operated at almost all operating conditions (e.g. wide range of the engine speeds and loads), and is able to capture some transient behaviour of the powertrain as well as the steady state response. Moreover, the parametric formulation of each component in the proposed powertrain model makes the model more efficient to simulate different types of powertrain (e.g. for a passenger car or truck).
Acceleration and Heating of Metal Particles in Condensed Matter Detonation
(University of Waterloo, 2010-04-30T17:11:18Z) Ripley, Robert
For condensed explosives containing metal particle additives, interaction of the detonation shock and reaction zone with the solid inclusions leads to non-ideal detonation phenomena. Features of this type of heterogeneous detonation are described and the behaviour is related to momentum loss and heat transfer due to this microscopic interaction. For light metal particles in liquid explosives, 60-100% of the post-shock velocity and 20-30% of the post-shock temperature are achieved during the timescale of the leading detonation shock crossing a particle. The length scales corresponding to particle diameter and detonation reaction-zone length are related to define the interaction into three classes, bound by the small particle limit where the shock is inert, and by the large particle limit dominated by thin-detonation-front diffraction. In particular, the intermediate case, where the particle diameter is of similar order of magnitude to the reaction-zone length, is most complex due to two length scales, and is therefore evaluated in detail. Dimensional analysis and physical parameter evaluation are used to formalize the factors affecting particle acceleration and heating. Examination of experimental evidence, analysis of flow parameters, and thermochemical equilibrium calculations are applied to refine the scope of the interaction regime. Timescales for drag acceleration and convective heating are compared to the detonation reaction time to define the interaction regime as a hydrodynamic problem governed by inviscid shock mechanics. A computational framework for studying shock and detonation interaction with particles is presented, including assumptions, models, numerics, and validation. One- and two-dimensional mesoscale calculations are conducted to highlight the fundamental physics and determine the limiting cases. Three-dimensional mesoscale calculations, with up to 32 million mesh points, are conducted for spherical metal particles saturated with a liquid explosive for various particle diameters and solid loading conditions. Diagnostic measurements, including gauges for pressure, temperature, and flow velocity, as well as mass-averaged particle velocity and temperature, are recorded for analysis. Mesoscale results for particle acceleration and heating are quantified in terms of shock compression velocity and temperature transmission factors. In addition to the density ratio of explosive to metal, the solid volume fraction and the ratio of detonation reaction-zone length to the particle diameter are shown to significantly influence the particle acceleration and heating. A prototype heterogeneous explosive system, consisting of mono-disperse spherical aluminum particles saturated with liquid nitromethane explosive, is studied to develop fitting functions describing the shock compression transmission factors. Results of the mesoscale calculations are formulated into a macroscopic physical model describing an effective shock compression drag coefficient and Nusselt number. The novel models are explored analytically and are then applied to two challenging sets of test cases with comparison to experiment. Heterogeneous detonation is considered for aluminum particles saturated with liquid nitromethane, and inert particle dispersal is studied using a spherical explosive charge containing steel beads saturated in nitromethane. Finally, discussion of practical considerations and future work is followed by concluding remarks.
Accumulative fold-forging (AFF) as a novel severe plastic deformation process to fabricate a high strength ultra-fine grained layered aluminum alloy structure
(Elsevier, 2018-02-01) Khodabakhshi, Farzad; Gerlich, Adrian P.
A novel severe plastic deformation (SPD) process termed accumulative fold forging (AFF) is introduced to fabricate a homogenous ultra-fine grained (UFG) layered metal structure by repetitive folding and forging aluminum alloy foil. The present work studies AFF applied to thin foils of AA8006 Al-Fe-Mn aluminum alloy after 26 folding steps to produce a UFG structure containing 67,108,864 layers across a 2mm thickness. The structure of the layers and grain refinement are studied using X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM) and scanning-transmission electron microscopy (STEM) analysis. The results indicate a well-bonded inter-layer structure with an average grain size of about 200nm parallel and 250nm perpendicular to the forging direction, while dislocation density increased to ~7.2×1015m−2 following AFF. The mechanical strength of the aluminum foil is evaluated in the terms of indentation hardness testing before and after AFF process. The processed UFGed layered material exhibited an average hardness value of ~61.5 Vickers as compared to the initial value of ~30.4 Vickers for the annealed foil alloy, which indicates an improvement of ~100% due to the contributions of grain refinement, work hardening and interfacial strengthening of the bonded layers.
Accuracy Improvement for Measurement of Gas Diffusivity through Thin Porous Media
(University of Waterloo, 2012-08-31T20:02:43Z) Dong, Lu
Accurate measurement of the gas diffusion coefficient through porous media is of significant interest to science and engineering applications including mass transfer through soils, building materials, and fuel cells to name a few. Accurate measurements are necessary for simulation and optimization of complex systems involving gas transport. The Loschmidt cell, or closed tube method has been extensively used to measuring the binary gas diffusion coefficient of gas pairs. Recent studies have used a modified Loschmidt cell with an additional porous sample to measure the effective diffusion coefficient through the porous sample. The method employs what is called the resistance network method for calculating the effective diffusion coefficient through the porous sample. In this study, a one-dimensional simulation was developed to evaluate the accuracy of the resistance network method with a modified Loschmidt cell. Dimensionless parameters are shown to be applicable for both the conventional Loschmidt cell as well as the modified Loschmidt cell with the porous sample. A parametric simulation study was performed to show that the error relates closely to the ratio of diffusive resistances of the sample and bulk gas denoted as the resistance ratio, Ω*. With a simulated experimental duration of 250s, which is typical of experiments in literature, the error was found to be negligible when Ω* < 0.1 but increased dramatically for Ω* > 0.1 up to a maximum of approximately 20% error. The equivalent Fourier number, Fo_eq, based on the equivalent diffusivity, D_eq, was proposed as an approximate expression for the degree to which the concentration gradient in the test cell has evolved. It was found that the error has nearly a linear relationship with Fo_eq. Since a lower Fo_eq means a less decayed profile with significant transience remaining, as Fo_eq drops, the the error increases. By controlling the simulation test length for different thickness and diffusivity samples such that Fo_eq = 12.5, the error was reduced to less than 1% over most of the range of parameters and less than 6% over the full range of parameters spanning two orders of magnitude for both thickness and diffusivity. The resistance network method requires the measurement of the sample thickness, a diffusion length, and two diffusion coefficients using with the modified Loschmidt cell (one with the porous sample and one without). Analysis found that the equation used for calculating the effective diffusion coefficient, D_eff, through the porous sample inherently magnifies the relative uncertainty of the measured values in the final calculated value for D_eff. When Ω* < 1, the percentage uncertainty in both diffusion coefficient measurements could potentially be magnified by one or more orders of magnitude. To mitigate uncertainty in D_eff, Ω* must be greater than 1 to ensure that the uncertainty is magnified by no more than a factor of 2. This study recommends that modified Loschmidt experiments aim for Ω* = 1 and Fo_eq = 12.5 to greatly reduce the error and uncertainty in the measurement of D_eff.
Accurate determination of interface trap state parameters by admittance spectroscopy in the presence of a Schottky barrier contact: Application to ZnO-based solar cells
(AIP Publishing, 2013-04-14) Marin, Andrew T.; Musselman, Kevin P.; MacManus-Driscoll, Judith L.
This work shows that when a Schottky barrier is present in a photovoltaic device, such as in a device with an ITO/ZnO contact, equivalent circuit analysis must be performed with admittance spectroscopy to accurately determine the pn junction interface recombination parameters (i.e., capture cross section and density of trap states). Without equivalent circuit analysis, a Schottky barrier can produce an error of similar to 4-orders of magnitude in the capture cross section and similar to 50% error in the measured density of trap states. Using a solution processed ZnO/Cu2O photovoltaic test system, we apply our analysis to clearly separate the contributions of interface states at the pn junction from the Schottky barrier at the ITO/ZnO contact so that the interface state recombination parameters can be accurately characterized. This work is widely applicable to the multitude of photovoltaic devices, which use ZnO adjacent to ITO.
ACL Strain During Single-Leg Jump Landing: An Experimental and Computational Investigation
(University of Waterloo, 2019-01-11) Polak, Anna
The anterior cruciate ligament (ACL) is a commonly-injured ligament in the human knee joint. ACL injury repair is a costly procedure; however, left unrepaired, ACL injuries can lead to complications later in life. In order to understand ACL injury, metrics such as strain in the ACL are measured under various loading conditions. A motion which has potential to cause ACL injury, a single leg jump landing, was replicated and ACL strain was recorded. Two common approaches for this purpose are in-vitro studies involving cadavers, and finite element (FE) modelling of the knee joint. Once ACL strain during the potentially injurious motion is evaluated, it is easier to work towards potential improvements to protective or rehabilitative equipment, such as knee braces. The objective of the current study was to measure ACL strain during a single leg jump landing using two different methods: 1. In-vitro experiments involving cadavers: - ACL strain vs. time was measured with unbraced and braced cadaver knees. 2. Finite element modelling of the human knee: - The finite element model was assessed using the in-vitro experiments, and can potentially be used to evaluate braced knee conditions in the future. The inputs for the experiments and finite element model were taken from motion capture, which was done in-vivo on two participants in a previous study. The two participants provided input kinetics and kinematics of a single-leg jump landing. The kinematic and kinetic inputs were then applied to three cadaveric specimens using the dynamic knee simulator (DKS) at the University of Waterloo, and ACL strain relative to the beginning of the trial was measured. The cadaver knees were also tested wearing an Össur CTi Custom knee brace, and the effect of the knee brace on relative ACL strain was measured. A finite element model of the human knee joint was also investigated by extracting the right leg of an existing full human body model, the Global Human Body Model Consortium (GHBMC) average-sized male (M50) model, and updating some of the tissue mechanical properties. The same boundary conditions from the experimental iv study were applied to the GHBMC right leg model, and relative ACL strain was calculated and compared against the experimental data. The experimental maximum relative ACL strain for an unbraced full jump landing was 0.032 and 0.057 for participant #1 input and 0.062 for participant #2 input. The computational maximum relative ACL strain was 0.042 for participant #1 input and 0.139 for participant #2 input. The finite element model was able to replicate the experimental ACL strain vs. time curves reasonably well, with a mean squared error of less than 0.01 for all loading scenarios. The results of the unbraced vs. braced jump landing experiments showed that the knee brace had no effect on ACL strain. The mean squared error between unbraced and braced ACL strain vs. time curves was less than 0.0011 for all loading cases, which is a low error value when compared to strains in the range of 0.015- 0.089. The jump landing finite element model is an important first step in using finite elements to predict relative ACL strain during jump landing. Future research directions include study of factors affecting ACL strain, incorporating the knee brace into the finite element model to investigate possible improvements to the brace, and investigating the benefits of adopting a subject-specific geometry for the model.
Active Aerodynamic Modification of Wind Turbine Blades to Reduce Load Fluctuation
(University of Waterloo, 2020-04-16) Samara, Farid
Wind turbines operate predominantly in relatively unsteady flow conditions and are typically misaligned with the incoming wind. Moreover, as wind turbines increase in size, the loading on the blades becomes more problematic and obstructs the development of larger and more efficient wind turbines. In this project, a trailing edge flap (TEF) is used to develop an active control strategy to attenuate load fluctuation on the blades in normal environmental conditions. Wind turbine load fluctuation reduction techniques could increase the power produced by the turbine, reduce the capital and maintenance cost while prolonging the life span of not just the blades but the drivetrain and tower. An experimental 3.5 m diameter wind turbine rig was designed and tested in a large scale wind generation facility operating at different tip speed ratios, blade pitch angles and yaw angles. The instrumentation of the compact blade was capable of measuring rotor torque, flapwise/edgewise blade root bending moment, and normal force coefficient at r/R=0.66 and 0.82. Two custom-built actuation systems were capable of oscillating the pitch and flap independently to create an active control strategy. The blade is of constant pitch and chord of 178 mm while the TEF covers 20% of the chord and 22% of the 1.47 m aerodynamic blade span. First, a 2D experimental campaign showed how the TEF is fully capable of controlling the airfoil aerodynamics statically and during dynamic stall. It is concluded that even though the TEF was not capable of controlling the formation of the leading edge vortex (LEV), it was however capable of reducing its magnitude and more importantly, a reduction in cyclic loading. Second, a comprehensive and a detailed set of results showed how the rotor torque, flapwise/edgewise blade root bending moment, and normal force coefficient at multiple r/R locations change under different yaw angles, pitch angles, tip speed ratio and TEF angles. When possible the results were compared to numerical models such as the NREL OpenFast code to increase confidence in the results and provide essential conclusions to improve the models. It was found that in non-yawed conditions, OpenFast predictions were accurate but discrepancies start to emerge when the turbine is yawed and operating in dynamic stall conditions. Finally, the pitch and TEF were continuously actuated in separate tests to determine the effectiveness of each system at reducing load fluctuation on a yawed wind turbine. The reduction in load fluctuation due to the TEF and the pitch systems were found to be between 45%-65% and 65%-80% respectively. The data presented throughout this thesis provides a methodical and comprehensive argument to support the use of TEF on a utility-scale turbines to reduce load fluctuation and fatigue levels at the blade root. It also provides insight on the effects of dynamic stall, stall delay and 3D flow induced by the blade rotation on an operating wind turbine.
Active and Semi-Active Bushing Design for Variable Displacement Engine
(University of Waterloo, 2006) Arzanpour, Siamak
The Variable Displacement Engine (VDE) is a new generation of engines that are designed to decrease the fuel consumption at the cruise speed of a vehicle. The isolation of the VDE's new vibration pattern is beyond the capabilities of conventional mounts and bushings. Consequently, in this thesis, novel active and semi-active solutions are proposed to develop various semi-active and active hydraulic bushing proof-of-concept systems that may solve the isolation problem in a VDE system.

The dynamic stiffness response, which is the transfer function that relates the engine displacement to the transmitted force, is normally used as the key design criterion for engine mounts and bushings. In this thesis, a linear mathematical model of a conventional hydraulic bushing is purposed. The validity of the mathematical model is confirmed by an experimental analysis, and the various parameters in the dynamic stiffness equation are evaluated. The experimental results indicate that the dynamic stiffness frequency response of the conventional hydraulic bushing has both soft and stiff regions. The soft region is limited to low frequencies. For the VDE isolation, the goal is to provide a soft bushing for a wider range of frequencies than a conventional bushing can accommodate. Addition of a short inertia track, similar to a decoupler used in conventional hydraulic engine mounts, may be used to extend the soft region of a conventional hydraulic bushing, and the experimental results validate it.

Since the short inertia track provides no additional damping, a supplementary Magnetorheological (MR) valve is also devised. The MR valve has the advantage to minimize the amount of MR fluid used, which significantly reduces the cost of the overall system. The novel valve allows the damping coefficient of the bushing assembly to be controlled by varying the electrical current input to a solenoid coil. A mathematical model is derived for the MR bushing, and is validated experimentally.

In addition, an active bushing to solve the VDE isolation problem is purposed in this thesis. In this bushing, a magnetic actuator, composed of a permanent magnet and a solenoid coil, is included in the active bushing. This active chamber affects the dynamic stiffness response of the bushing by altering the bushing's internal pressure. The nonlinear equation of motion of the permanent magnet is linearized and is incorporated into the new mathematical model of the system. The new purposed model for the active bushing is in good agreement with the experimental results. This active chamber is also proved capable of producing complex dynamic stiffness frequency response.

The conclusion is that the proposals in this thesis can contribute to the isolation of the vibration pattern, imposed by the application of a VDE system.
Actuation Techniques For Frequency Modulated MEMS Gyroscopes
(University of Waterloo, 2015-01-23) Xie, Michael
This thesis focuses on the design and implementation of an analog actuation circuit for a novel frequency-modulated MEMS gyroscope. The gyroscope detects angular rotations as the difference between the natural frequencies of two closely spaced drive and sense modes rather than the magnitude of displacement in the sense direction. Furthermore, the actuation system features a resonant drive (RLC) circuit that amplifies the gyroscope actuation signal. The input to the circuit is an amplitude-modulated (AM) signal composed of a carrier signal modulated with a base signal that excites the gyroscope drive mode. The carrier frequency corresponds to the electrical resonance frequency of the drive circuit. This research develops techniques for the stabilization of the circuit output through close loop feedback. First, we attempt to increase the signal-to-noise ratio of the modulating signal by implementing feedback and feedforward control loops (AGC). The feedback controller closes the loop on the entire conditioning circuit for the modulating signal while the feedforward controller acts on the input signal to the conditioning circuit. The feedforward and the feedback controllers derive an error signal representing the signal noise by comparing the input and output signal, respectively, with a reference signal. However, we find that the breadboard circuit implementations of our control strategies performed similar to a baseline uncontrolled function generator due to the additional noise input from the breadboard and the additional components used to implement the controller, such as the amplifiers. Next, we develop a single-harmonic amplitude-stabilized actuation scheme for the gyroscope to minimize multi-frequency excitations and reduce amplitude fluctuations to improve the gyroscope precision. A low pass filter is applied to the AM signal to obtain a single sideband full carrier (SSB-FC) signal. Since the capacitance of RLC circuit changes due to the vibration of the gyroscope, this variation in capacitance causes a shift in the frequency response of the RLC circuit, resulting in variation in the circuit gain. Three feedback control topologies are implemented to stabilize the signal by first detecting the change in signal level, and then amplifying or attenuating the signal level in order to maintain a constant gyroscope actuation level. The control strategy with the best performance involves feeding back the RMS of the output signal to control the amplitude of the carrier signal and feeding back the average of the output signal’s envelope to control the bias level of the modulating signal. Using control this strategy, the peak magnitude at the carrier frequency dropped approximately 2% as the capacitance is varied from 15 pF to 16 pF, awhile the other two control strategies changed 9% and 6%.
Adapting Regenerative Braking Strength to Driver Preference
(University of Waterloo, 2023-12-13) Marrone, John Francis
The modern automotive industry has witnessed a growing emphasis on adapting the driving experience to individual drivers. With the rising popularity of electrified vehicles, the implementation of regenerative braking systems, specifically lift-off regenerative braking, has become a focal point. However, research indicates that drivers often find the predefined deceleration response during lift-off regenerative braking to be undesirable. This thesis addresses this issue by developing an adaptive regenerative braking controller that learns driver preferences, thereby fulfilling the objective of enhancing the driving experience of lift-off regenerative braking systems by reducing driver fatigue through the minimization of pedal interventions. The research focuses on three critical aspects: accurate identification of driving conditions, acquisition of driver preferences for lift-off regenerative braking, and compatibility with real-time automotive hardware. By leveraging advanced techniques like HDBSCAN clustering, fuzzy logic inference, and online Q-learning, the research achieves accurate driving condition identification and adaptation to individual driver preferences in a control scheme that can be practically deployed in-vehicle. Real-world testing demonstrates the controller's 80.9 % accuracy in identifying driving conditions as well as its successful learning of the driver's preferred deceleration to within 1.9 %. Subsequently, the adaptive regenerative braking controller results in a 23.2 % reduction in pedal interventions during deceleration compared to a baseline that is representative of an industry-standard implementation of lift-off regenerative braking. This outcome underscores the controller's potential to alleviate driver fatigue and enhance the overall driving experience. This research contributes to the advancement of electrified vehicle powertrain control, focusing on improving driver acceptance and satisfaction with regenerative braking systems.
Adaptive and Interconnected Suspension Systems for Improving Truck Stability and Ride Quality
(University of Waterloo, 2023-08-08) Lu, Yukun
Truck drivers are constantly exposed to undesirable vibrations caused by uneven road surfaces, especially in long-distance transportation. In addition to being at risk of repetitive motion injuries, drivers also suffer from fatigue, which in turn becomes a potential safety issue. As a way to resolve the issue, a truck is usually equipped with two suspension systems, namely the primary suspension and the secondary (cabin) suspension, in which the cabin suspension mainly acts as a vibration isolation system between the cabin and the rest of the vehicle. Different techniques have been applied to the cabin suspension to improve ride quality, stability, and safety. In most commercial vehicles, conventional passive suspensions are used that contain passive springs and dampers with fixed stiffness and damping properties. Nowadays, adaptive suspension systems are developed to further improve ride quality by dynamically controlling damping characteristics. Besides, interconnected suspension systems have been introduced to enhance the roll stability of the sprung mass and provide better handling and ride quality simultaneously. As a result, this study aims to improve truck drivers’ ride comfort and stability by developing semi-active and interconnected suspension systems. A semi-active cabin suspension system is developed based on different multi-objective optimal control approaches to attenuate the vertical, roll, and pitch vibrations transmitted to the cabin. The Model Predictive Control (MPC) is chosen as the benchmark because of its superior performance in handling constraints and prediction, although its high computational costs make it difficult to be implemented in suspension applications. To solve this issue, a novel integrated Skyhook-LQR (Linear Quadratic Regulator) control approach is introduced to take advantage of both Skyhook and LQR while its computational cost is low enough for real-time implementation in suspension control tasks. In addition, two gain-adaptive algorithms are proposed to intelligently adjust the control gains according to the disturbance inputs and/or vehicle states based on onboard sensor measurements. Two novel interconnected suspension systems are designed to minimize the harsh rotational motions during braking or turning maneuvers, namely AIS-ARS and AIS-ARPS. Both configurations have adaptive damping and adjustable rotational stiffness characteristics, which provide excellent vibration attenuation and attitude control performances. All the proposed suspension systems and their mathematical models are examined and validated through laboratory experiments and co-simulations between ADAMS/Car and MATLAB/Simulink.
Adaptive and Optimal Motion Control of Multi-UAV Systems
(University of Waterloo, 2019-05-21) Koksal, Nasrettin
This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations and experiments on a multi-quadrotor UAV system testbed.
Adaptive Cooperative Highway Platooning and Merging
(University of Waterloo, 2017-05-19) Sancar, Feyyaz Emre
As low-cost reliable sensors are introduced to market, research efforts in autonomous driving are increasing. Traffic congestion is a major problem for nearly all metropolis'. Assistive driving technologies like cruise control and adaptive cruise control are widely available today. While these control systems ease the task of driving, the driver still needs to be fully alert at all times. While these existing structures are helpful in alleviating the stress of driving to a certain extent, they are not enough to improve traffic flow. Two main causes of congestion are slow response of drivers to their surroundings, and situations like highway ramp merges or lane closures. This thesis will address both of these issues. A modified version of the widely available adaptive cruise control systems, known as cooperative adaptive cruise control, can work at all speeds with additional wireless communication that improves stability of the controller. These structures can tolerate much smaller desired spacing and can safely work in stop and go traffic. This thesis proposes a new control structure that combines conventional cooperative adaptive cruise control with rear end collision check. This approach is capable of avoiding rear end collisions with the following car, as long as it can still maintain the safe distance with the preceding vehicle. This control structure is mainly intended for use with partially automated highways, where there is a risk of being rear-ended while following a car with adaptive cruise control. Simulation results also shows that use of bidirectional cooperative adaptive cruise control also helps to strengthen the string stability of the platoon. Two different control structures are used to accomplish this task: MPC and PD based switching controller. Model predictive control (MPC) structure works well for the purpose of bidirectional platoon control. This control structure can adapt to the changes in the plant with the use of a parameter estimator. Constraints are set to make sure that the controller outputs are always within the boundaries of the plant. Also these constraints assures that a certain gap will always be kept with the preceding vehicle. PD based switching controller offers an alternative to the MPC structure. Main advantage of this control structure is that it is designed to be robust to certain level of sensor noise. Both these control structures gave good simulation results. The thesis makes use of the control structures developed in the earlier chapters to continue developing structures to alleviate traffic congestions. Two merging schemes are proposed to find a solution to un-signaled merging and lane closures. First problem deals with situations where necessary levels of communication is not present to inform surrounding drivers of merging intention. Second structure proposes a merging protocol for cases where two platoons are approaching a lane closure. This structure makes use of the modified cooperative adaptive cruise control structures proposed earlier in the thesis.
Adaptive Formation Control of Cooperative Multi-Vehicle Systems
(University of Waterloo, 2015-12-22) Guler, Samet
The literature comprises many approaches and results for the formation control of multi-vehicle systems; however, the results established for the cases where the vehicles contain parametric uncertainties are limited. Motivated by the need for explicit characterization of the effects of uncertainties on multi-vehicle formation motions, we study distributed adaptive formation control of multi-vehicle systems in this thesis, focusing on different interrelated sub-objectives. We first examine the cohesive motion control problem of minimally persistent formations of autonomous vehicles. Later, we consider parametric uncertainties in vehicle dynamics in such autonomous vehicle formations. Following an indirect adaptive control approach and exploiting the features of the certainty equivalence principle, we propose control laws to solve maneuvering problem of the formations, robust to parametric modeling uncertainties. Next, as a formation acquisition/closing ranks problem, we study the adaptive station keeping problem, which is defined as positioning an autonomous mobile vehicle $A$ inside a multi-vehicle network, having specified distances from the existing vehicles of the network. In this setting, a single-integrator model is assumed for the kinematics for the vehicle $A$, and $A$ is assumed to have access to only its own position and its continuous distance measurements to the vehicles of the network. We partition the problem into two sub-problems; localization of the existing vehicles of the network using range-only measurements and motion control of $A$ to its desired location within the network with respect to other vehicles. We design an indirect adaptive control scheme, provide formal stability and convergence analysis and numerical simulation results, demonstrating the characteristics and performance of the design. Finally, we study re-design of the proposed station keeping scheme for the more challenging case where the vehicle $A$ has non-holonomic motion dynamics and does not have access to its self-location information. Overall, the thesis comprises methods and solutions to four correlated formation control problems in the direction of achieving a unified distributed adaptive formation control framework for multi-vehicle systems.
Adaptive Model Predictive Control for Microstructure Control in Laser Material Processing
(University of Waterloo, 2024-09-16) van Blitterswijk, Richard Hendrik
Laser material processing (LMP) has revolutionized traditional fabrication methods across industries, evolving from laser cutting to encompassing advanced techniques like laser heat treatment (LHT), laser welding, and laser additive manufacturing, enabling precise alteration of material properties and unprecedented design freedom across industries. However, achieving consistent material characteristics remains a significant challenge, particularly in advanced additive manufacturing processes such as laser-directed energy deposition (LDED), where the complex interplay between process parameters and material properties hinders uniform product quality, emphasizing the need for advanced process control strategies. Conventional control methods like proportional-integral-derivative controllers struggle to anticipate the intricate interactions inherent in LMP processes, making it difficult to control multiple parameters simultaneously. Model-based control strategies, leveraging numerical models, offer promise in providing a comprehensive understanding of process dynamics. However, their practical implementation in real-time control applications is impeded by the computational challenges of numerical models. Overcoming these obstacles is crucial to harnessing the full potential of numerical models for enhanced process control and ensuring consistent, reproducible material characteristics. In this research, a novel adaptive model predictive control (AMPC) algorithm was developed to address the challenges of ensuring consistent material characteristics in LMP processes. Initially, a two-dimensional (2D) adaptive thermal model was designed for real-time prediction of thermal dynamics during the LHT process, focusing on parameters like peak temperature and spatial cooling rate. Subsequently, a one-dimensional (1D) adaptive thermal model was developed with improvements on efficiency, accuracy, and suitability for control applications compared to the 2D counterpart, focusing on real-time prediction of the temperature distribution and spatial cooling rate. Additionally, a model predictive control (MPC) algorithm utilizing a 2D thermal model was developed for single-input single-output (SISO) peak temperature control during LHT to improve the consistency of hardness and hardening depth. Finally, an AMPC algorithm was designed using the 1D adaptive thermal model for multi-input multi-output (MIMO) temperature and spatial cooling rate control during LDED to achieve consistent material characteristics throughout the process. A series of LHT and LDED experiments were designed to assess the real-time thermal dynamic prediction capabilities of the models and the real-time control capabilities of the MPC algorithms in LMP. These experiments encompass open-loop LHT and LDED scenarios, targeting the validation of adaptive 1D and 2D thermal models, respectively. Additionally, closed-loop LHT and LDED experiments were designed to investigate the efficacy of the MPC algorithms in controlling one or multiple process parameters to achieve consistent hardness values. The 2D adaptive thermal model effectively adjusted to the thermal dynamic changes in real-time, yielding precise predictions of peak temperature and spatial cooling rates during LHT. Similarly, validations of the 1D adaptive thermal model showcased near-perfect temperature and cooling rate predictions during LDED, along with impressive computational efficiency. Utilizing the SISO MPC algorithm ensured consistent hardness and hardening depth through closed-loop peak temperature control during LHT. Meanwhile, deploying the MIMO AMPC algorithm enabled consistent hardness across the entire deposition process. This was achieved by simultaneously controlling the temperature and spatial cooling rates during the LDED experiments. In conclusion, this research marks significant advancements in real-time process control within LMP applications. Through the integration of adaptive thermal models and MPC algorithms, the study achieves the crucial objective of ensuring consistent material characteristics in LMP-manufactured parts. The developed AMPC algorithm demonstrates unprecedented levels of control, stability, and reliability. Moreover, its versatility and simplicity extend its applicability beyond LMP processes, enabling adoption in various advanced manufacturing processes utilizing concentrated energy sources. Thus, the AMPC methodology holds the potential to address the crucial need in advanced manufacturing by ensuring consistent and reproducible material characteristics in manufactured parts across the entire industry.

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