Graduate Projects (Mechanical Engineering)

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Powertrain layout and component design with topology optimization for an electric truck
(2025) Deng, Liang; Dong, Zuomin
This report presents the design, optimization, and prototyping of an electric medium-duty truck (eMDT) retrofitted from a Toyota Dyna, addressing challenges in spatial constraints, weight distribution, and structural integrity. The project focuses on developing an optimized powertrain layout, lightweight structural components, and efficient integration of electric powertrain systems to meet standard and performance requirements. Reverse engineering was employed to create a detailed CAD model of the chassis, facilitating the analysis of spatial constraints and component placement. The powertrain layout was modelled and analyzed in terms of weight distribution and payload capacity. Structural modifications to the chassis and mounting systems were validated using finite element analysis (FEA). The motor bracket design underwent topology optimization using the Solid Isotropic Material with Penalization (SIMP) algorithm combined with hyperparameter optimization (HPO) to achieve a 48% weight reduction while maintaining structural reliability under operational loads. The project demonstrated the effectiveness of integrating advanced computational techniques with practical engineering to overcome the challenges of vehicle electrification. Key outcomes include an optimal powertrain layout, validated structural modifications, and a lightweight motor bracket design. These contributions advance the development of sustainable, efficient, and cost-effective electric medium-duty trucks, laying the groundwork for future vehicle electrification innovations.This report presents the design, optimization, and prototyping of an electric medium-duty truck (eMDT) retrofitted from a Toyota Dyna, addressing challenges in spatial constraints, weight distribution, and structural integrity. The project focuses on developing an optimized powertrain layout, lightweight structural components, and efficient integration of electric powertrain systems to meet standard and performance requirements. Reverse engineering was employed to create a detailed CAD model of the chassis, facilitating the analysis of spatial constraints and component placement. The powertrain layout was modelled and analyzed in terms of weight distribution and payload capacity. Structural modifications to the chassis and mounting systems were validated using finite element analysis (FEA). The motor bracket design underwent topology optimization using the Solid Isotropic Material with Penalization (SIMP) algorithm combined with hyperparameter optimization (HPO) to achieve a 48% weight reduction while maintaining structural reliability under operational loads. The project demonstrated the effectiveness of integrating advanced computational techniques with practical engineering to overcome the challenges of vehicle electrification. Key outcomes include an optimal powertrain layout, validated structural modifications, and a lightweight motor bracket design. These contributions advance the development of sustainable, efficient, and cost-effective electric medium-duty trucks, laying the groundwork for future vehicle electrification innovations.
Investigating the effect of boundary excitation on the orientation behavior of non-spherical grains using the Discrete Element Method (DEM)
(2024) Naamnh, Saeed; Nadler, Ben
Non-spherical grains have been progressively receiving attention from the research communities and industry due to their natural occurrence and relevance in engineered applications. These grains display complex behaviors that are associated with different applications such as agriculture and the pharmaceutical industries. However, they also pose significant challenges such as jamming when passing through constricted pathways. Most existing studies on granular materials have focused on spherical grains, emphasizing grain size rather than shape and orientation, particularly in relation to grain boundary interactions. Studies have shown that the mechanical properties of non-spherical grains are significantly influenced by their alignment. This has been demonstrated through various simulations and experimental investigations. This study investigates the orientation behavior of non-spherical grains in response to oscillating boundaries using the Discrete Element Method (DEM). The results reveal that boundary excitation plays a pivotal role in influencing grain alignment, offering new insights into how excitation drives grain alignment. It is observed that as the boundary excitation increases the degree of alignment decreases, indicating a strong dependence of orientation behavior on excitation parameters such as frequency. Additionally, the variations in grain shape is found to significantly influence the alignment.
Building Energy Simulation vs Actual Energy Consumption and Impacts of Climate Change
(2024) Saha, Ram Krishna; Valeo, Caterina; Mukhopadhyaya, Phalguni
Energy modeling is necessary to determine the energy consumption of buildings and identify ways to reduce it. HOT2000 is an energy simulation modeling software developed and maintained by Natural Resources Canada that plays a pivotal role in Canada's home energy rating, labeling, and code compliance systems. This research examines the energy performance gap between modeling and actual energy consumption in two detached houses, located in Vancouver, BC were modeled with HOT2000 software. The architectural drawings were obtained from a design farm. It was observed that the actual energy consumption of the homes exceeded the predicted values by 40 to 45%. The discrepancies were attributed to the limitations of the energy modeling program, inconsistencies between the energy model and the actual buildings, and additional energy loads in the homes. Additionally, the study considers building performance under future climate scenarios, predicting an increase in energy consumption. Furthermore, this study conducted a parametric analysis of wall construction and energy sources to enhance energy efficiency. With just the change of energy source for space heating from Gas Boiler to Air Source Heat Pump (ASHP) the energy consumption dropped and saved 15 to 35% and CO2 decreased from 45 to 75% per year. Improving the wall R-value from R-14 to R-28 the space heating energy saved around 12 to 15%. Based on the energy modeling results, the South-facing house in Vancouver, BC, is more energy-efficient (~5%) than the north-facing house. Climate change is expected to intensify temperature extremes and fluctuations, which will likely increase the need for combined cooling and heating energy.
Instant identification of bacteria species using integration of colorimetric sensing arrays and deep learning (Mostafa – Akbari – Karan, MAK - 1)
(2024) Singh, Karanvir; Akbari, Mohsen
The research delves into the integration of colorimetric sensors in detecting volatile organic compounds (VOCs) for rapid bacterial identification through advanced machine-learning algorithms. With the use of a colorimetric sensor array that detects any VOCs in the form of a chemical change, we were able to establish a methodology. The pattern was formed and further deep analysis of this pattern to produce homogeneity in results was the goal. This method uses optoelectronic arrays to process RGB data, allowing for highly specific bacterial sample separation. Artificial intelligence frameworks are used in the creation and testing to improve detection capabilities and increase accuracy even with little data. The final ANN model utilized for the image classification was able to produce 92% accuracy within 2 minutes after utilizing a training sample of 235 samples and testing it on 10% of data throughout the span of 2 months. The results of the findings extend to clinical diagnostics, where accurate detection might facilitate targeted treatments and expedite pathogen identification. The results indicate potential for practical application, providing a robust tool for non-invasive bacterial classification.
A comparative analysis of mould growth on exterior sheathing of a brick masonry wall in different Canadian climate zones
(2024) Singh, Jasveer; Mukhopadhyaya, Phalguni; Valeo, Caterina
This study investigates the risk of mould growth on sheathing boards in brick masonry walls in four Canadian cities: Vancouver, Ottawa, Calgary, and Saskatoon. The hygrothermal simulation tool WUFI® Pro 6.8 (1D) and the VTT Mold Index were used to conduct this investigation. The impact of moisture penetration through brick veneer cladding on the potential for mould growth in Oriented Strand Board (OSB), Fiberboard (FB), and Plywood (Ply) sheathing was assessed. For hygrothermal simulations, a severe weather year was selected based on a 31-year historical weather dataset (1986-2016) using the severity index (Isev) method prescribed in the ASHRAE Standard 160-2021. The calculation period was set for seven years, and two wall orientations were considered: (i) direction with the least solar radiation and (ii) maximum wind-driven rain direction. For each orientation, three rain penetration cases (1%, 2% and 3% of wind-driven rain) were considered, and two Air Change Rates (ACH 0 and ACH 15) were considered in the drainage cavity for each of the three rain penetration cases. As per ASHRAE 160-2021, the rain penetration was deposited on the outer layer of the water-resistive barrier (WRB). The results showed that for the 1% rain penetration and no ventilation, the mould growth index (MGI) for all three sheathing boards remained at zero (i.e., No mould growth) for Vancouver’s north-oriented wall (least solar radiation); however, the southeast-facing wall (maximum wind-driven rain) experienced a higher MGI (up to 5.3). For the same case (i.e. 1% rain penetration), the remaining simulated cities experienced MGI>5 (i.e., 50% visually covered surface). In the case of increased rain penetration and no ventilation, each sheathing board’s mould growth performance significantly decreased (MGI>5) for all four cities in both orientations; however, an air change rate of 15/hour (ACH 15) in the drainage cavity reduced the mould growth (MGI<1, local growth microscopic level) in Calgary, Ottawa and Saskatoon. In contrast, ACH 15 was insufficient to reduce the MGI < 3 (i.e., visuals of mould <10% surface coverage) for the Vancouver location, except for the 1% rain penetration case.
Smartphone enabled biomarker sensing and on-demand drug delivery using 3D printed hollow microneedle arrays
(2024) Ninan, Joel; Akbari, Mohsen
Remote health monitoring and disease treatment are pivotal in advancing health equity, reducing geographical and socioeconomic barriers, and providing universal access to quality care. By enabling continuous, personalized healthcare, this paradigm addresses disparities, offering timely interventions for individuals in underserved or remote locations. Microneedle arrays (MNAs) stand at the forefront of this revolution, enabling painless, minimally invasive access to interstitial fluid for both diagnostics and drug delivery. This paper presents a groundbreaking theranostic wearable system, leveraging digital light processing (DLP) 3D-printed hollow microneedle arrays fabricated using PEGDA hydrogel, equipped with colorimetric sensors for the quantitative analysis of key biomarkers, including pH, glucose, and lactate, directly from the skin's interstitial fluid. The system incorporates a remotely activated, smartphone enabled, ultrasonic atomizer-driven mechanism for on-demand drug delivery, enhancing portability by eliminating the need for complex mechanical pumps. This integrated approach simplifies point-of-care treatments and expands the possibilities for remote patient management. The accompanying smartphone application seamlessly interfaces with the system, enabling real-time monitoring and drug administration. Demonstrated results include precise detection of pH (3–8 mM), glucose (up to 16 mM), and lactate (up to 1.6 mM), as well as enabling the effective administration of drugs in response to biomarker fluctuations. The system's drug delivery performance was validated using on-demand on/off tests and its biocompatibility using a scratch assay, highlighting its potential for treating chronic diseases requiring sustained therapy. This innovative platform not only addresses key challenges in drug delivery but also opens new pathways for non-invasive health monitoring, offering a transformative solution for the long-term management of chronic conditions.
Methane pyrolysis evaluation for low-carbon hydrogen production: A comparative techno-economic analysis
(2024) Serrato Arias, Cinthia; Andrew, Rowe
In recent years, various hydrogen production pathways have been explored to support net-zero strategies and climate objectives. Methane pyrolysis has emerged as a low-carbon hydrogen technology with promising potential to compete with electrolysis and steam methane reforming processes. This process utilizes thermal decomposition to convert methane into hydrogen gas and solid carbon, effectively avoiding CO₂ emissions during production. A tubular plug flow reactor model was used to evaluate the reactor simulation, focusing on its kinetic parameters and operating conditions. This research evaluates three scenarios, each designed for a hydrogen production capacity of 50 tons per day, exploring two carbon mitigation strategies which are carbon capture and storage (CCS) and the use of an electric arc furnace (EAF). Among these scenarios, Case 1 exhibits the highest environmental impact at 4.14 kg CO2/kg H2 due to its lack of decarbonization strategy. A techno-economic assessment reveals that Case 1 has the lowest levelized cost of hydrogen (LCOH) at 2.50 USD/kg H₂, whereas Case 2 with CCS unit presents a LCOH of 2.87 USD/kg H₂, these two options offer competitive hydrogen prices comparable with SMR with CCS. The implementation of EAF in Case 3 exhibits the highest cost at 3.27 USD/kg H₂, although remains more cost-effective than electrolysis. Methane pyrolysis pathway has demonstrated its potential as a viable low-carbon hydrogen production, where Case 2 and Case 3 provide economic feasible option with minimal carbon emissions.
Development of Sustainable Konjac Glucomannan-Based Microcarriers for Cultivated Meat Production
(2024) Singh, Satinder; Akbari, Mohsen
The global demand for sustainable alternatives to conventional meat production has promoted advancements in cultivated meat technologies, with scaffolding materials playing a key role in supporting cell growth and mimicking natural meat structures. This study investigates konjac glucomannan (KGM), a plant-based polysaccharide, as a biocompatible and cost-effective material for microcarrier generation in cell culture technologies. A method was developed to synthesize KGM hydrogels and fabricate microcarriers via controlled acidic degradation and crosslinking with epichlorohydrin (ECH) using a water-in-oil emulsion technique. The resulting microcarriers demonstrated excellent biocompatibility, mechanical stability, and a reticulated structure that may support cell adhesion and proliferation, competing with conventional dextran-based microcarriers while offering cost and sustainability benefits. These findings highlight KGM's potential as a cruelty-free microcarrier material for cultivated meat production and other biomedical applications, supporting the objectives of ethical innovation and global sustainability.
Analyzing the environmental impacts of imported insulation materials: A comparative study in a Canadian residential building
(2024) ding, yangyang; Valeo, Caterina; Mukhopadhyaya, Phalguni
This study examines the life cycle environmental impacts of different insulation materials used in residential buildings in Vancouver, with a particular focus on the A1-A4 stages 1 raw material extraction(A1), transportation to manufacturing (A2), manufacturing processes(A3), and transport to the construction site(A4). Under the CleanBC mandate to reduce greenhouse gas emissions by 40% by 2030, addressing both operational carbon (B1-B6) and embodied carbon (A1-A5) is crucial, particularly as embodied carbon is becoming a larger portion of total lifecycle emissions. This shift occurs because operational carbon can be reduced incrementally each year through improvements in building mechanical system efficiency. As a result, focusing on reducing embodied carbon during the design and construction phases is essential to achieving long-term sustainability goals in building lifecycle assessments. Through a comparative analysis of insulation materials sourced from the United States and Europe, this study examines their Global Warming Potential (GWP), Ozone Depletion Potential (ODP), and Acidification Potential (AP) using Life Cycle Assessment (LCA), such as Athena Impact Estimator, openLCA. The findings indicate that U.S.-sourced insulation materials, such as rock wool and cellulose, generally exhibit lower environmental impacts across most metrics in the A1-A4 stages compared to European materials. U.S.-sourced cellulose consistently shows reduced GWP, ODP, and AP, making it a more sustainable choice for Canadian building applications. However, European materials demonstrate advantages in Ozone Depletion Potential (ODP) in certain cases, highlighting the significant influence of regional production and transportation processes on environmental performance. The insights from this study offer a valuable basis for architects, engineers, and policymakers to make informed material sourcing decisions, thereby contributing to the broader goals of decarbonization and sustainable construction in Canada.
A microfluidics device integrated with Surface Enhanced Raman Spectroscopy (SERS) for characterizing microplastics in aqueous samples
(2024) Vahidi, Mohsen; Akbari, Mohsen
Microplastic contamination is an emerging contaminant and concern that can be found all over the planet. These microplastics are often very tiny in size; therefore, they can readily pass though bedrock and infiltrate water bodies such as rivers, lakes, and seas. Whenever such environmental contamination occurs, the first step in order to address the issue is to characterize the contamination in order to define its origin. This project proposes a design of a microfluidic chip, which is integrated with a Surface Enhanced Raman Spectrometer to characterize microplastic particles in various aqueous solutions such as water. The proposed design is capable of sorting and collecting microplastics based on their size without any need for a membrane. It also has a flat architecture, which makes it easy to manufacture at a reasonable cost. SolidWorks was used for the computer aided design (CAD) of the microfluidic chip and COMSOL Multiphysics was utilized for computer aided engineering (CAE) calculation to verify the design. According to the calculations, this microfluidic chip is capable of size-based sorting of microplastics.
Comparative Analysis of Various National Building Codes and Carbon Payback Periods of Insulation Materials at Different Climate Zones in Canada
(2024-05-31) Mascarenhas, Alastair Alphonse; Valeo, Caterina; Mukhopadhyaya, Phalguni
Single-family dwellings make a significant contribution to carbon emissions in Canada. The National Energy Code for Buildings (NECB) emphasizes reducing the operational carbon consumption of buildings. Using thermal insulation material in constructing building envelopes plays a crucial role in decreasing a building's operational carbon. However, since insulation materials have embodied carbon, therefore, for optimal building performance and design, designers should take into account both the operational and embodied carbon of insulation materials. This paper compares the embodied carbon and operational energy savings resulting from the use of thermal insulation material. It also presents Carbon Payback Period (CPP) values of different thermal insulation materials in various Canadian cities representing different climate zones. A model is created using the Athena Impact Estimator (AIE) tool, based on a three-bedroom single-family home with a wood-frame structure. Three insulation materials, namely Batts Fiberglass, Blown Cellulose and Mineral Wool, are evaluated in three different cities, namely Vancouver, Toronto and Calgary, representing three climate zones (zones 4, 5 and 7a). The HOT2000 energy simulator calculates operational carbon consumption using the energy mix comprising electricity and natural gas. The CPPs for selected materials were calculated using operational and embodied carbon data. A comparison of the Whole Building Life Cycle Analysis (WBLCA) Global Warming Potential (GWP) between the National Building Code (NBC) 1995 and 2020 versions revealed an average 25% decrease in Operational Carbon and an average 6% increase in Embodied Carbon. This compromise showed a shift towards standardizing energy-efficient buildings and selecting sustainable thermal insulation materials for construction. Identifying and using less carbon footprint materials can help reduce embodied carbon. In Calgary, the CPP for Blown Cellulose, Batts Fiberglass and Mineral Wool insulation were calculated to be 0.92, 0.94 and 1.09 years, respectively. In Toronto, the CPP for Blown Cellulose, Batts Fiberglass and Mineral Wool is 1.15, 1.17 and 1.39 years, respectively. Vancouver has longer CPP for Batts Fiberglass, Blown Cellulose and Mineral Wool with 2.66, 2.64, and 2.69 years, respectively. This indicates that as the heating degree days (HDD) increases, the CPP shortens. Graphing the CPP vs HDD can help designers and contractors make more informed decisions regarding the available choices of thermal insulations.
Evaluation of Ride Comfort and Road Holding for Heavy Vehicle Suspension (HVS) through Model Predictive Controller (MPC) based on Hybrid Semi-Active Damping Strategy
(2024) Faronbi, Michael O.; Shi, Yang
The continuous expansion of industrial demand in various countries has increased the need for large commercial vehicles to transport products between locations. As a result, freight transportation has become a key driver of economic growth, contributing significantly to a country's GDP, typically accounting for 6-12% of the total. However, this rapid growth in road transportation has also brought about a rise in traffic congestion and a higher probability of road accidents. According to a European Union assessment, large vehicles are a significant factor in these incidents. Nevertheless, the primary cause of road accidents remains driver negligence. Work-related injuries and disorders caused by whole-body vibration have been extensively studied worldwide. To address this problem, researchers have developed a pitch plane model of a large vehicle using a Lagrangian approach coupled with various hybrid semi-active damping schemes based on the model predictive control (MPC) framework. The MPC-based suspension controller is designed to optimize comfort and handling by minimizing a quadratic cost function. The focus has been on reducing the vertical accelerations experienced by the vehicle due to variations in the vehicle and road profile to improve the vehicle's stability and ride comfort level. Additionally, managing the changes in vertical force encountered by each tire during its interaction with the road has been crucial. The ride comfort of the driver has been evaluated by analyzing the vertical accelerations at the center of gravity of the pitch plane model, both with and without the MPC-based controller, using the guidelines specified in ISO 2631-1/2. Simulation results have demonstrated the impact of the MPC-based controller, with and without its implementation, on the ride comfort level and road-holding capability of the heavy vehicle system. These findings highlight the potential of the MPC-based controller to enhance the overall performance of heavy vehicle systems in terms of ride comfort and road holding.
Literature review of 3D-bio printed hair follicles and the proposal for a permanent hair system on the scalp
(2024) Issac, Mathews; Shi, Yang
Modern hair restoration surgery helps restore hair loss or bald areas, which requires a substantial number of hair follicles from the donor area. However, in some cases, people do not have sufficient donor hair follicles for transplant surgery due to diseases, genetics, aging, other biological and environmental issues, and so on. This problem can be addressed using 3D bioprinter technology to cultivate artificial hair follicles. This project report meticulously reviews six different methods for artificially cultivating hair follicles (HF) using bio cells and a cell-transforming environment created using 3D bioprinting technology. The six methods were 3D-bioprinting of a gelatin-alginate hydrogel for tissue-engineered hair follicle regeneration, tissue engineering of human hair follicles using a biomimetic developmental approach, bead-jet printing enabled sparse mesenchymal stem cell patterning augments skeletal muscle and hair follicle regeneration, robot-assisted in situ bioprinting of gelatin methacrylate hydrogels with stem cells induces hair follicle-inclusive skin regeneration, bioprinting of hair follicle germs for hair regenerative medicine, and using bioprinting, and spheroid culture to create a skin model with sweat glands and hair follicles. The main disadvantages of these experimental methods are their complexity, the significantly low number of hair follicles generated, and the fact that it will take time to get approval for human trials for these new technologies. The report also proposes a procedure to overcome the disadvantages of artificially grown HF by developing a permanent hair system on the scalp.
An integrated temperature control system for a 3D printed droplet generation microfluidic device HC-BAR Chip
(2024) Bhatt, Sheshank; Akbari, Mohsen
A microfluidic chip is a small device which deals with a very small amount of fluid. It has microscale channels. It has been used in different fields of science like engineering, physics, biochemistry, etc. A droplet generator is a microfluidic device which is capable of generating small droplets which is used in different applications like drug delivery, cell trapping and gene analysis. Temperature control is an essential part of droplet generation, and it affects the generation of droplets. This project proposes a microfluidic chip design (HC BAR Chip) with a uniform distribution of temperature with no embedded heating equipment. The chip is capable of creating heating and cooling zones unaffected by each other with a flow-focusing droplet generation method. CAD software like Solidworks is used to design and COMSOL Multiphysics® software for the analysis.
Simulation & Formation Control for Leader- Follower Wheeled Mobile Robots Based on Embedded Control Technique
(2023-12-19) Jayasingha Appuhamilage, Chathusanka
Formation control has garnered significant attention from researchers in recent times. This heightened interest can be attributed to its applicability in a wide range of tasks, including but not limited to search and rescue operations, agricultural coverage jobs, and area patrols. This surge in attention is primarily attributed to its ability to enhance efficiency, reliability, and the capacity to accomplish complex tasks effectively within these domains. Formation control for ground vehicles has particularly been useful for application such as cargo transportation, cooperative manipulation, and surveillance and exploration and many more [2]. Combining sensors on robots in a formation enables them to scan larger areas more quickly by directing sensors in different directions, surpassing the smaller area of coverage of a single robot can achieve during the same time. This enhances the efficiency of the search and exploration process compared to individual robot operations. For this project, a formation control strategy based on the embedded control technique for a leader-follower system was used. The proposed technique divides the formation control problem into two subtasks, which is different from the traditional design philosophy of basing the formation controller design directly on the formation tracking errors [3]. Two subtasks are virtual signal generator and trajectory tracking controller. The virtual signal generator achieves the desired formation control goal and outputs a reference signal to the trajectory tracking controller of the follower [3]. The embedded control technique reduces the complexity of directly implementing formation tracking errors while providing several other benefits as well. A predesigned mobile robot model in CoppeliaSim was used as the leader and follower. The robots were programmed to implement the controller and simulate the system. Finally, a number of tests were performed adjusting gains and observing the performance of the robots to identify the optimal performance gain values. Gains were adjusted with the goal of minimizing the error and reducing the motion jerk of the follower.
High-Performance Brick Mortar Mix to Optimize Moisture Management in Brick Wall
(2023-08-16) XIA, HAI; Valeo, Caterina; Mukhopadhyaya, Phalguni
The durability of exterior building envelopes is significantly impacted by the presence of water, particularly through the capillary rise mechanism that allows liquid water to penetrate building materials. This process affects both the energy efficiency and durability of buildings. To assess the capillary water intake into porous building materials, the water absorption coefficient is used as a characterization parameter. Additionally, the water vapor permeability of a material indicates its ability to allow moisture to diffuse and escape. In this project, two concentrations of zinc stearate (0.5% w/w and 1% w/w) were added to commonly used mortar. Following the ASTM standard test procedure, the liquid water absorption coefficients and water vapor permeability of brick, mortars, and brick mortar joints were determined. These experimental values were utilized as inputs for the hygrothermal performance analysis (numerical modelling) of the brick wall assembly. The experimental findings suggest that the addition of zinc stearate to the mortar can reduce water absorption capacity while simultaneously enhancing water vapor permeability. Numerical modelling results further demonstrate that the use of high-performance brick mortar materials can significantly improve the moisture management capability for brick walls in the marine-warm and humid climate of Vancouver, BC, Canada.
Prediction of Orthogonal Cutting Forces Based on Multi-fidelity Modeling
(2023-04-26) Ahmadi, Keivan
Simplified analytical models of chip formation mechanics (e.g. the well-known Merchant’s model) are widely used to compute the machining forces in orthogonal cutting operations. The accuracy of analytical models, however, diminishes when the cutting edge has a rounded shape, known as edge (or hone) radius, which is common for most cutting tools. Finite element (FE) simulation can be used to obtain more accurate predictions of the forces in the presence of edge radius, but FE is computationally expensive because it should numerically solve a thermo-mechanical contact problem with nonlinear material properties to model the plastic deformation and damage of the workpiece. The high computational cost of FE simulations indeed becomes crucial when the force model is used for process optimization or for online simulations in the digital twin of the machining process. In this research, we present a computationally efficient data-driven model with acceptable accuracy when compared to the FE simulation. The presented model combines the predictions of FE simulations (i.e., high-fidelity dataset) and the predictions of the analytical model (i.e., low-fidelity dataset) and generates a new regression multi-fidelity model. The high-fidelity dataset is generated by an FE simulation in Abaqus and using Johnson-Cook constitutive equation to model the plastic deformation and damage of an aluminum workpiece during chip formation. The low-fidelity dataset is generated by Merchant’s analytical model. In both datasets, the inputs are the tool rake angle and uncut chip thickness, and the outputs are the cutting and feed forces. In total, 440 data points (40 high-fidelity points and 400 low-fidelity points) are generated. Based on this dataset, a multi-fidelity model is trained and tested through the emulator-embedded neural network (E2NN) method. The Root Mean Squared Error (RMSE) is then computed between the predictions of the trained model and the predictions from the FE simulation to quantify the performance of the presented multi-fidelity model. The results show a close agreement between the predictions of the high-fidelity and the multi-fidelity models. The computed RMSE was less than 8.5%. Yet, the accuracy would gradually improve by increasing the high-fidelity samples. Moreover, note that the computational time of a FE simulation is typically a few (~5) minutes while it is less than a second for the presented multi-fidelity model. The presented modelling approach therefore can efficiently replace high-cost FE simulations in process optimization or online simulations.
Structural Health Monitoring of the Marine Structure Using Guided Wave and UAV-based testing
(2023-04-25) Gupta, Yugansh; Shi, Yang
The marine industry encompasses a vast range of structures that can be challenging to access, and thus highly mobile systems can be useful for efficient structural health monitoring. This research aims to investigate the feasibility of using unmanned aerial vehicles (UAVs) for deploying various non-destructive testing (NDT) methods to inspect steel structures. In addition, we are evaluating piezoelectric patches (PZT) based detection systems that can provide early warnings of corrosion and fatigue cracks. The study analyzes the pitch and catches method using time-of-flight (TOF) to detect cracks and defects, the UAV-based hammer percussion test for frequency response, and the use of an infrared-mounted camera on the drone for NDT purposes. The goal is to identify the best approach for monitoring the health of marine structures.
The Boundary and Excitation Effect of Non-Spherical Granular Material
(2023-03-21) YASEEN, GHULAM; Nadler, Ben
Non-spherical grains have been gradually receiving attention from both researchers and the industry because of their behavior. Even though these grains possess complex macroscopic orientations that are associated with different applications, such as the pharmaceutical industry, they sometimes can also cause challenges, like jamming while passing collectively through certain narrowed passages. Most published articles have presented studies about granular materials, based on spherical grains and have mainly examined the grain size but ignored the grain’s shape and orientation, especially concerning the interaction of these grains with their boundaries. Further, literature reported that the mechanical properties of the granular materials are critically affected by the alignment of non-spherical grains as conducted in various simulations and associated experiments. To explore more about the shape and orientational effect of non-spherical grains with respect to boundaries, a detailed initial-level observational study is done with the help of different boundary shapes and grains ranging from elongated rice to long cylindrical grains. The collision of grains with boundaries generates an orientational field that results from their interaction with boundaries and neighboring grains. This research shows that the excitation of grains occurs due to their collision with boundaries, and these boundaries can play an important role in the orientation of non-spherical grains. The study provides ‘thought-provoking’ directions for exploring more about the orientation of non-spherical grains.
Impact on building energy performance by deployment of dynamic insulation in residential buildings in Canada
(2023-03-08) Shukla, Anoopkumar; Valeo, Caterina; Mukhopadhyaya, Phalguni
This report summarizes the results of an analysis evaluating the energy performance of small residential buildings in Canada. Using the HOT2000, an energy simulation modelling program created and maintained by Natural Resources Canada, the goal of this work is to investigate dynamic insulations, run simulations, and assess the possible energy savings brought on by using dynamic insulation materials (DIMs) in exterior walls in place of conventional static insulation. DIMs can alter their thermal properties based on control procedures, unlike conventional static insulations, to accomplish desired goals. In this analysis, exterior walls with DIMs are controlled to minimize heating and cooling thermal loads in residential buildings, located in different climate zones in Canada. In particular, 2-step manual controls are used to switch the R-value of variable insulation between low and high levels based on the thermal interactions between the outside and inside a prototypical one-story home, thereby reducing heating and cooling requirements while maintaining thermal comfort. According to the analysis's findings, dynamic insulations can drastically lower the amount of energy needed to run heating and cooling systems. The use of 2-step control techniques operating DIMs, in particular, can lower yearly energy consumption by up to 44% for space cooling and by up to 33% for space heating, resulting in up to 36% annual energy savings.

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