Mechanical and Mechatronics Engineeringhttp://hdl.handle.net/10012/99122024-03-29T14:52:39Z2024-03-29T14:52:39ZProcess Optimization, Numerical Modelling, and Microstructure Control in Laser Powder Bed Fusion of Ti-5553 PartsHasanabadi, Mahyarhttp://hdl.handle.net/10012/203952024-03-15T02:30:54Z2024-03-14T00:00:00ZProcess Optimization, Numerical Modelling, and Microstructure Control in Laser Powder Bed Fusion of Ti-5553 Parts
Hasanabadi, Mahyar
Additive manufacturing (AM) is an advanced production technique that creates components by depositing material layer by layer. AM has been deployed industrially for producing metallic parts from alloys which pose challenges in traditional manufacturing processes like titanium alloys (Ti-alloys). While Ti-alloys are widely utilized across industries due to their exceptional strength-to-weight ratio, corrosion resistance, and toughness, machining titanium products is a complex endeavour. Laser Powder Bed Fusion (LPBF) as a metallic AM method presents an optimal solution. LPBF has been recognized as an appealing fabrication process for producing metallic parts with customized properties, however, obtaining these properties is quite challenging due to the interaction of several independent parameters. The properties of an LPBF-made product are highly dependent on the process parameters, which directly impact the melting and solidification of the molten metal. Hence, an in-depth investigation into the effect of process parameters on the melting and solidification conditions is necessary for manufacturing a high-quality product with tailored properties.
The current research deals with LPBF of a recently developed Ti-alloy, Ti-5Al-5V-5Mo-5Cr (Ti-5553). Among Ti-alloys, the β-metastable Ti-5553 offers a wide processing window, good hardenability, and excellent heat treatability, making it a preferred material in the aircraft industry. To generate an LPBF process map for Ti-5553 and assess the influence of process parameters on the properties of printed parts, an integrated single-track to multi-layer method was systematically employed. An investigation into the track morphology, melt pool geometry and melt pool microstructure composted of single-tracks was compared with a range of microscopic examinations and X-ray computed tomography measurements to multi-layer tracks to create a reliable process map. Following that, additional investigations were conducted on properties like mechanical performance and surface roughness, providing the manufacturer with additional information from each set of process parameters in order guide selection of processing parameters.
Since some aspects of solidification, such as temperature gradient and solidification rate, are not easily measurable experimentally, numerical modelling can provide an efficient solution for studying the correlation between the process parameters and the geometrical and thermal conditions of the LPBF-made melt pool. Hence, a numerical heat transfer modelling with a novel hybrid volumetric heat source has been proposed to simulate the LPBF of Ti-5553 alloy for the first time. The developed hybrid model, with an incredibly low modelling error, can predict melt pool geometry and thermal variables, at different locations and time steps during melt pool solidification to estimate many important aspects of the microstructure formation such as grain morphology, subgrain size, and grain growth direction.
The gained knowledge from the experimental and numerical analyses of melt pool solidification under various process conditions is used to propose the “laser post-exposure treatment” as an innovative method for in-situ microstructure control during the LPBF process. The laser post-exposure (PE) treatment is a secondary laser scanning with significantly lower energy input, conducted after the completion of the main laser scanning strategy on the loose powder and before spreading the new layer of powder. This in-situ microstructure control treatment results in the development of uniform, uninterrupted, and elongated grains. A printed part utilizing post-exposure can be comparable to directionally solidified products used widely in industries for enhanced creep and fatigue resistance. It should be noted that this work is the first scientific attempt to control the grain structure via in-situ laser post-exposure.
2024-03-14T00:00:00ZSizing-Design Method and Performance Improvement for Adiabatic Compressed Air Energy Storage SystemsSarmast Sakhvidi, Sepidehhttp://hdl.handle.net/10012/203802024-03-07T03:31:02Z2024-03-06T00:00:00ZSizing-Design Method and Performance Improvement for Adiabatic Compressed Air Energy Storage Systems
Sarmast Sakhvidi, Sepideh
Electrification of the energy system through renewable sources is an effective solution to combat the adverse effects of climate change. Despite the potential, integrating renewables into the electrical grid faces a significant challenge due to their intermittent nature. This intermittency impedes a seamless transition to sustainable, low-carbon electricity systems. In response, grid-scale electrical energy storage (EES) systems facilitate the storage of surplus electricity generated during low-demand periods for subsequent use during peaks. Among various storage methods, compressed air energy storage (CAES) has gained attention for its mechanical nature spanning over four decades. The recent emergence of Adiabatic CAES (A-CAES) facilities, such as the Goderich deployment, emphasizes the need for advancements. A-CAES systems aim to overcome challenges linked to thermal energy storage (TES), which constrains the round-trip efficiency of these systems (TES in A-CAES systems stores compressed air heat for efficient energy recovery).
The present thesis delves into the pursuit of engineering utility-scale A-CAES systems, with a specific focus on system sizing and design considerations. The primary research objectives include introducing a novel CAES sizing method, designing a near-adiabatic CAES system with appropriate thermal energy storage size and design to improve the system performance, and evaluating the compatibility of small-scale CAES systems with wind-diesel systems for remote Canadian communities.
While prior research has explored configurations of A-CAES and TES to enhance round-trip efficiency, certain critical aspects have been overlooked. Previous studies lacked focus on 1) external factors like power grid fluctuations, 2) operational limits in CAES system sizing and design, and 3) challenges in A-CAES operation (as predicted efficiencies often failed during experiments). This thesis aims to address the gaps in the existing literature by investigating the reasons behind these limitations. Potential contributing factors include reliance on generic thermodynamic models, lack of power grid connectivity, neglect of heat losses, and flaws in system designs. The aim is to comprehensively tackle these issues by proposing the sizing and design of a Near-Adiabatic CAES (NA-CAES) system. This approach seeks to rectify the shortcomings identified in previous models and enhance the overall understanding and performance of A-CAES systems.
The first objective, fulfilled in Chapter 3, introduces a new CAES sizing method, the coverage-percentage method. This method builds upon the frequency-of-occurrence method, integrating time-dependent operational constraints, component limitations, and pressure considerations within a CAES reservoir. Applying this method to Ontario's electrical grid data optimally sizes compressors, expanders, and cavern capacities, significantly enhancing the accuracy of capturing excess energy.
The second objective, addressed in Chapter 4, explores the operational limits of A-CAES system components, particularly turbomachines and TES systems. The chapter addresses disparities between theoretical models and practical experiments, employing sensitivity analyses to optimize operational modes. This optimization aims to enhance overall system efficiency while minimizing the required volume of TES. Chapter 4 concludes by determining charging, idle, and discharging profiles for the reservoir and TES of the NA-CAES system, tailored for Ontario, bridging the gap between theory and practical implementation. The results highlight the practicality of the NA-CAES system with a round-trip efficiency exceeding 60%.
In Chapter 5, the study expands its scope by exploring the integration of a partially A-CAES (PA-CAES) system with wind-diesel systems in remote areas. Building on findings from Chapters 3 and 4, the research assesses the performance of a small-scale CAES system, emphasizing sizing, design, operation, and viability in isolated regions. Unlike previous studies focusing solely on diesel engine efficiency, this research analyzes power supply-demand patterns and assesses the full-year performance and feasibility of deploying PA-CAES within wind-diesel hybrid systems using an optimization-based sizing method.
To sum up the research findings, a three-year analysis of Ontario's electrical grid data and an assessment of 82,500 scenarios provide insights for determining the optimal size of a CAES system. The coverage-percentage method highlights the importance of economic considerations to avoid oversizing components. The study identifies that compressors and expanders between 30 MW and 70 MW, cavern energy capacity of 630 MWh to 770 MWh, can capture at least 42% of charging and 26% of discharging capacity in Ontario. Results show that increasing compressor and expander sizes enhance coverage percentages up to an optimal point.
For a NA-CAES system, it is recommended to use a multi-tank TES to efficiently capture compression heat. The ideal number of TES tanks corresponds to the number of expansion units. The choice of thermal fluid does not affect the optimal temperature for TES tanks but depends on the expander inlet temperature. Achieving this optimal temperature involves optimizing mass flow rates for charging and discharging TES fluid and sizing TES tanks appropriately. A constant-pressure reservoir in a CAES system offers greater utilization and flexibility compared to a constant-volume reservoir, allowing longer and more efficient operation periods.
Additionally, investigating the feasibility of an adaptive energy storage system for a remote Canadian community shows potential to reduce diesel fuel dependence. A specific CAES configuration for a remote community, e.g., a 300 kW compressor, 200 kW expander, and 18,000 kWh reservoir, achieves a 55% reduction in diesel fuel consumption, presenting cost-effective solutions (an initial investment of $5,000,000). Another configuration with a 400 kW compressor, 290 kW expander, and 39,000 kWh reservoir achieves a higher reduction of 63.4%, albeit with a greater initial investment of $10,000,000. These findings contribute to optimizing CAES for both grid applications and sustainable energy solutions in remote areas.
2024-03-06T00:00:00ZSmooth and Time-Optimal Trajectory Planning for Multi-Axis Machine ToolsDiCola, Katiehttp://hdl.handle.net/10012/203702024-02-27T03:30:53Z2024-02-26T00:00:00ZSmooth and Time-Optimal Trajectory Planning for Multi-Axis Machine Tools
DiCola, Katie
This thesis presents novel methods for feedrate optimization and toolpath smoothing in CNC machining. Descriptions of the algorithms, simulation test cases, and experimental results are presented.
Both feedrate optimization and toolpath smoothing are essential for increasing manufacturing efficiency while retaining part quality in CNC machining. The application of high-speed machining also necessitates the use of high feedrates, and smooth toolpaths which can be safely traversed at high feeds.
However, problems occur when the feedrate is increased without check. High tracking error in machining may cause part tolerance errors. Transient vibrations due to jerky movement can lead to poor part surface quality. High speed trajectories may also demand greater torque than what the feed drives are capable of producing, which affects the motion controller’s ability to follow the trajectory correctly. The condition of the machine is also a concern, with the potential for damage or excessive wear on the machine’s components, if excessive axis velocity or jerk (i.e., rate of change of acceleration) is commanded.
The feedrate scheduling algorithm developed in this thesis combines linear and nonlinear programming in a dual-windowed implementation. Linear programming (which is computationally fast) is used to quickly provide a near-optimal guess, based on axis velocity, acceleration, and jerk constraints. The solution is then refined through the use of nonlinear optimization. In the latter step, requiring more computations, the commanded motor torque and expected servo error are constrained directly, leading to shorter movement time. A windowing alignment procedure is presented which allows for these two optimization methods, each with different problem constraints and solutions horizons, to work in tandem with one another without risking infeasible boundary conditions between the windows. The algorithm is validated in simulation and experiment studies. Case studies analyzing the parameters of the optimization algorithm are also presented, and the configuration which is most computationally efficient is determined.
A toolpath generation method is presented in which Euler-spiral pairs are used to smooth sharp corners, with an algorithm that integrates directly with the developed feedrate optimization The result is an exactly arc-length parametrized, G2-continuous toolpath whose axis derivatives can be computed very efficiently, which helps reduce the overall computation time.
A repositioning toolpath method is also developed to reduce the cycle time of multi-layer contouring operations. This method replaces circular arc based repositioning segments between contouring passes (commonly used in industry) with a smooth Euler spiral based curve. This avoids tangent and curvature discontinuities, allowing for smoother motion with lower velocity and acceleration demands, while also reducing the overall motion. The repositioning toolpath has also been integrated with feedrate optimization and validated in simulation results.
2024-02-26T00:00:00ZBrain Response to Overpressure and Recoil Loads from Discharge of Long-Range Precision RifleMaldonado Echeverria, Javier Andreshttp://hdl.handle.net/10012/203332024-02-03T03:31:03Z2024-02-02T00:00:00ZBrain Response to Overpressure and Recoil Loads from Discharge of Long-Range Precision Rifle
Maldonado Echeverria, Javier Andres
The presence of concussion-like symptoms related to overpressure exposure and recoil forces from long-range precision rifle (LPR) training has been reported in the literature. However, the recoil head kinematics, overpressure loadings from LPR discharge, and the interaction of the two load paths have not been previously quantified.
In the present study, experiments were undertaken by the Defense Research and Development Canada (DRDC) Valcartier Research Centre, using an instrumented head form to measure the overpressure from LPR discharges and to measure head kinematics resulting from recoil using instrumented mouthguards on human volunteers. The measurements included a high-speed video to enable estimation of the relative onset timings of overpressure and recoil head kinematics. The LPR configurations encompassed both muzzle suppressor and non-suppressor configurations. Then, planar finite element (FE) head models (in the sagittal and transverse planes) were used to quantify the effects of the measured loadings on the brain response. The models were used to simulate three boundary conditions: only the overpressure, only the recoil head kinematics, and combining the two loadings to investigate the interaction of the load paths.
The overpressure resulting from discharge of the LPR was reduced significantly when the suppressor configuration was employed. The overpressure reached the head 3.6 ms after exiting the barrel of the LPR, with peaks ranging from 0.2 to 27.6 kPa with and without suppressor, respectively. The onset of recoil head kinematics varied between operators, occurring between 7.4 to 24.4 ms after the onset of overpressure loading to the head.
In addition, the FE models showed that the intracranial pressure response predicted in the head demonstrated an interaction between overpressure and head kinematics, while strain in the brain was largely governed by recoil head kinematics.
The results of this study provide important information regarding the relative severities and interaction between the overpressure and recoil head kinematics in LPR operators.
2024-02-02T00:00:00Z