Keynote Speakers 

Abstract

In this presentation, two applications of rheological measurements will be illustrated: one in packaging sealing and the other on swelling in gels. In the first study, Elongational rheological measurements on various polyethylene resins (linear and branched) were used to evaluate the linear viscoelastic elongational viscosity and its correlation to molecular weight and adhesion strength. The results also showed that melt toughness, i.e. the area under the stress-strain curve in extensional flow, correlates well with the plateau sealing temperature, probably due to long chain branching.

In the second application, rheological measurements were used on smart hydrogels that can respond to external stimuli. In this study, we developed a fibrous structured poly(Nisopropyl acrylamide) (PNIPAM) hydrogel and characterized its rheological behavior in swollen and shrunk states under different temperatures. Under small-amplitude oscillatory shear, we found that both storage and loss moduli were at least 8 times higher in the shrunk state compared with the swollen state. We also investigated the elastic response behavior through compression of the hydrogel using rheometry. We were able to detect the swollenshrunk transition temperature of the hydrogel through monitoring the force change of the hydrogel as a function of temperature in the rheometer.

Abstract

This keynote explores the optimization of compliance and mass minimization in 3D-printed polymers fabricated using fused filament fabrication (FFF). By integrating topology optimization (TO) with print direction optimization, substantial improvements in mechanical performance can be achieved. TO enables significant mass reduction, cutting production costs while optimizing print orientation, enhancing stiffness, further reducing mass and forming a closed-loop design approach. 

Although extensive research has been conducted separately on TO and print direction optimization, limited efforts have combined these techniques. Current commercial software lacks integrated tools for coupling topology and print orientation optimization. In this work, we present an in-house tool, "TPO" (Topology and Print Optimization), developed to address mass and compliance minimization problems using the method of moving asymptotes (MMA). MMA ensures robust optimization with guaranteed convergence and allows for the introduction of new design variables, offering flexibility for future enhancements. 

Our methodology investigates mass and compliance minimization problems in 3D-printed polymers, highlighting the distinct outcomes of each approach. Using the modified solid isotropic material with penalization (SIMP) method, we evaluate trade-offs between compliance and mass reduction to identify optimal parameters for achieving desired mechanical properties. The results demonstrate the efficacy of the TPO code in delivering significant improvements in the performance of 3D-printed polymers, contributing to advanced design and manufacturing practices in additive manufacturing.  

Abstract

Isolated and remote Indigenous communities in the Canadian Arctic face major energy transition challenges, but the situation can also present some opportunities for them. 

Over the last decade, our team has been involved more specifically in the region of Nunavik, which is the northern portion of the province of Quebec. Nunavik has a population of 14,000 (90% of whom identify as Inuit) living in 14 small villages located along the Hudson Bay, Hudson Strait, and Ungava Bay. These Inuit communities are not connected to the provincial power grid, and each one relies on a diesel power plant to supply electricity to the buildings. Space heating is provided from fuel oil furnaces. Due to the local context, the ongoing energy transition resonates differently in Nunavik. Inspiring decarbonization efforts are intertwined with objectives such as self-determination aspirations and energy security issues.  

In this talk, we will start by summarizing the current energy situation in Nunavik, focusing on climatic, geographical, and social context, energy sources, building characteristics and energy demand profiles, and ongoing initiatives related to the energy transition. 

We will then discover some of the recent research works related to the energy transition in Nunavik, including ours and that of others. The results from a detailed building monitoring campaign will be described, showing the role of occupants and of envelope thermal anomalies on the energy demand. Other tests conducted in the field will be discussed (e.g., PV, geothermal). Different analyses and simulation results offering decarbonization avenues will be explored, including waste heat recovery options. We will show the importance of qualitative research, for example, with semi-structured interviews and workshops, to inform and guide engineering decisions and research efforts. 

Research with, for, and by Indigenous communities often requires a different approach or stance than what engineers are used to. We will humbly share some of our personal experiences in that respect. 

Abstract

As we have moved from Industry 1.0 to 5.0, the number of design objectives facing engineers has certainly more than quintupled.  Sustainability and circularity concerns have recently been added to the list of design objectives and constraints.  These objectives are easy to define in the abstract, but difficult to define concretely, and perhaps even more difficult to implement.  This presentation will try to address both challenges. 

This presentation will survey the current challenges facing engineers, with examples from design, manufacturing, and logistics.  We will discuss actionable definitions of sustainability and circularity.  In light of those goals, we will provide an overview of methods and tools available, focusing on life cycle assessment, which underlies most quantitative approaches.  Finally, the examples will help to illustrate not only the application, but the value, of integrating sustainability and circularity perspectives into design. 

The audience will develop basic fluency about key concepts in sustainability circularity and will be ready to implement sustainability thinking in their work.  With the discussion of methods and tools, the audience will also be primed to dive deeper in future. 

Abstract

Industry 4.0 (I4.0) relies on smart production systems, also knows as smart factories (SFs), that integrate advanced technologies like artificial intelligence (AI), internet-of-Things (IoT), and automation to enable adaptive, efficient, and data-driven decision-making across the production lifecycle. The goal is to facilitate mass personalization (MP), which combines product customization with mass production efficiency. This transformation has also had a profound impact on supply chain management (SCM) practices, emphasizing the need for interconnectivity and seamless communication in these value chains. 

This talk will cover several recent works from my research team on data-driven decision support tools for supply chain (SC) and operations planning in I4.0 manufacturing networks. The first line of research will uncover the challenges involved in the SC design and planning for MP. We specifically investigate several uncertain factors involved in the manufacturing of customizable modular-structured products, such as order size, design features, and technological limitations of suppliers at different SC echelons. Relatedly, the crucial role of collaborative SC design and planning as a mechanism to enhance reconfigurability, operational efficiency, and customer satisfaction will be discussed. Our research, particularly, promotes the idea of resource sharing among the firms that are active in parallel value chains via designing efficient collaborative decision support tools and benefit-sharing mechanisms. Finally, our recent attempts in integrating predictive maintenance with production planning in SFs will be discussed that relies on leveraging the data obtained from embedded sensors on the machines towards real-time monitoring of their condition and production rate.  

The talk will be concluded by summarizing future avenues of research on embedding AI algorithms into the state-of the-art optimization tools to advance real-time and data-driven planning in the fast-changing manufacturing landscape.  

Abstract

Currently, practically all land, marine and air transport is powered entirely by internal combustion (IC) and jet engines, with 95% of transportation energy coming from liquid fuels made from petroleum. Although the past few years have witnessed a surge in interest in the electrification of transportation, current alternatives to IC engines face significant barriers to unlimited expansion, which explains why 85–90% of transport energy is projected to continue to be derived from conventional liquid fuels powering combustion engines even well into the 2040s. Although engine researchers and manufacturers have targeted fuel consumption and pollutant emissions reduction for years, IC engines are still associated with massive emissions of greenhouse gas (GHG) (with the transportation of goods and people accounting for around 25% of global CO2 emissions from fossil fuel combustion) and pollutants, including unburnt hydrocarbons and particulate matter (PM). Soot, which refers to the carbonaceous particles issued from the high-temperature fuel-rich incomplete combustion of hydrocarbons, is subject to increasingly stringent regulations due to its harmful impacts on climate and human health. Indicated as a major factor in global warming, soot also drastically impacts air quality, and, as such, causes serious public health and safety issues. However, meeting current and incoming regulations aimed at restricting PM emissions issued from practical combustors requires identifying technological avenues in the fields of combustion chamber design and fuel formulation, hence prompting the need for a clarification of the impact of the composition and structure of hydrocarbon fuels on soot formation mechanisms, among others. Although the last half-century has seen major progress in the field, additional work is more than ever required, especially when it comes to using alternative fuels such as biomass-derived oxygenated substitutes, which have proved to constitute a positive soot suppression force. 

In view of the forgoing, the aim of this presentation is to briefly review the current state of knowledge on the sooting propensity of a variety of oxygenated additives considered as sustainable alternative transportation fuels for use in spark ignition, diesel and gas turbine engines. After presenting a brief summary of the different steps involved in the formation of combustion-generated particles, the main indexes proposed in the literature to assess the propensity to soot of conventional fuels and biofuels (the threshold soot index (TSI), the oxygen extended sooting index (OESI), the yield sooting index (YSI) and the fuel equivalent sooting index (FESI)) will be introduced. The main trends issued from the use of the latter to characterize the soot suppressing effect of various oxygenated additives will then be summarized, along with the conclusions drawn in a series of insightful experimental works conducted in laminar and turbulent combustion media. Note that the emphasis herein will be placed primarily on alcohols and esters, which are commonly considered for blending with gasoline and diesel fuel, as well as on molecules such as aldehydes and ketones, which exhibit a strong ability to reduce soot formation. Note also that due to the growing interest in alternative biomass-derived molecules, such as furans and terpenes, for their potential use as jet fuel substitutes, the recent works conducted to assess the sooting tendency of these compounds will also be surveyed. To conclude, an overview perspective will be proposed on the key areas, including the development of predictive sooting tendency models, where further studies are needed to ultimately enable the identification and/or formulation of fuel blends from different chemical functionalities, providing a strong lever for reducing soot emissions at the exhaust of combustion-based transportation systems.  

Abstract

Additive manufacturing (AM) techniques have recently gained much attention in different industries including medical, aerospace, energy, and defence. This is mainly due to several advantages that these methods present including shorter lead time and fewer design complications. Of particular interest is metal additive manufacturing techniques that compared to conventional counterparts offer improved mechanical properties due to hierarchical and ultrafine microstructures resulting from high solidification rates. AM has not yet received enough recognition in the marine sector (specifically shipbuilding) due to some challenges. More shipbuilding and ship repair contracts have been granted in recent years in Canada and more offshore oil and gas exploration projects have been initiated lately in North America. These new projects are the driving force to implement new technologies including AM, cyber physical systems, machine learning, and automation in the next generation of marine products. Some of the challenges with the adoption of AM in the marine sector are lack of certification procedures, the absence of reliable large volume AM production platforms, and access to trained highly qualified personnel. In addition, there is a huge interest to conduct scientific practices (including multiscale modeling, electron microscopy, and in-situ monitoring) to implement AM parts in the marine sector due to increasing requirements for superior mechanical, corrosion, fatigue, and impact properties in this sector. An overview of these opportunities and challenges along with an outlook of AM in the marine sector in Canada is presented.  

Abstract

Microrheology offers distinct advantages for measuring the micromechanical properties of interfaces. The length scale introduced by a colloidal probe ensures high sensitivity in probing interfacial rheological behaviour. Additionally, its ability to capture heterogeneities, velocity correlations, and rapid transient dynamics makes interfacial microrheology particularly valuable for studying structured interfaces, biological films, and 2D phase transitions. However, our theoretical understanding remains fragmented, lacking a unified framework and largely confined to specific cases. Moreover, the applicability of the Generalized Stokes-Einstein-Sutherland Relationship at fluid-fluid interfaces remains an open question. 

In this talk, we first discuss our recent progress in using interfacial (passive) microrheology to map micromechanical heterogeneities of complex interfaces. We show that heterogenous interfaces are found in various type of interfaces such as asphaltene-laden interfaces, 2D colloidal crystals and biofilms.  

Motivated by these findings, we then propose a theoretical framework for two-point interfacial microrheology. Specifically, we study the case of a Newtonian flat interface modelled by a Boussinesq-Scriven constitutive equation. Extending the work of Levine and MacKintosh (PRE, 2002), we consider the general case of an isothermal asymmetric system where the surface tension changes linearly with the surface-active molecule concentration. An unsteady convection-diffusion equation governs the concentration of active molecules. To model two-point microrheology, we consider one bead driven on a flat fluid-fluid interface by a periodic external force and we study the dynamics of a second bead at a given distance. The driven bead is modelled as an oscillatory point force, which lies in the plane of the interface. We obtain analytical solutions for the deformation field, the single particle power spectrum as well as the longitudinal and transversal pair correlation functions. These quantities are directly extracted by two-point-microrheology data in experiments. 

Our theoretical framework facilitates the transient analysis of interfaces containing surface-active molecules. Furthermore, the proposed framework can be extended to incorporate more complex constitutive equations or transport dynamics, further enhancing interfacial microrheology as a powerful characterization technique. 

Abstract

Computer-aided design (CAD) is used to conceptualize every manufactured object in our lives, from medical devices to cars to toys to furniture, and promises faster and higher-quality design. As CAD platforms align with software development tools that foster collaboration, a pivotal question emerges: 

Can the highly collaborative design processes of software development be applied to hardware product design? 

This keynote will review current research which applies software development principles, like pair programming and version control, to hardware design using CAD. Through laboratory experiments and analysis of innovation competition data, we can reveal important implications for how collaborative tools can positively impact design, management, and innovation in mechanical engineering product design. 

Abstract

The Wind Energy Institute of Canada (WEICan) is a research institute that has owned and operated a heavily instrumented 10 MW wind farm for more than 12 years. WEICan’s wind farm is in a high wind/high capacity factor environment that sees extreme weather events. As a research organization, we are interested in collaborating with likeminded organizations to advance the industry’s knowledge in asset management, service life estimation/investment decisions, and grid integration of renewable energy.  

This presentation will outline some issues we have had with our turbines, including with blades, gearboxes, and generators; and note how we addressed the issues and the research opportunities that have developed as a result of the issues.  

We will also outline our projections into future performance and availability, considering the impact of factors including inflation on the original business model; no original equipment manufacturer (OEM) to provide support; component OEMs no longer making the major components we use; high capacity factor on the turbines, component by component; extreme weather events; and revision of maintenance practices. 

Abstract

Metallic glasses accommodate most of their macroscopic plastic deformation through the activation of shear bands. These shear bands, however, first need to form before they can get activated, and the mechanisms of how this happens are still researched. To help fill this gap, we systematically investigated the deformation behavior of Pt57.5Cu14.7Ni5.3P22.5 metallic glass under micro-/nanopillar compression, where pillars were prepared using a novel method based on thermoplastic forming. This manufacturing method not only produces better-defined pillar geometries with lesser structural flaws that previous methods yielded, but it also enables the fabrication of a large number of identical pillars. At higher strain rates, local yielding happens in the areas featuring the biggest flaws due to a lack of time to properly accommodate the external pressure, which causes the distribution of yield loads to become more scattered. Interestingly, fracture stress exhibited a different pattern, showing no significant strain rate sensitivity. Additionally, annealed pillars displayed more closely clustered fracture loads, consistent with the understanding that annealing-induced structural relaxation enhances atomic packing, reduces defects, and increases resistance to compression. Overall, the findings suggest a three-phase deformation mechanism, where the pillars first deform elastically until plastic deformation starts in less dense areas of the pillar. This plastic deformation evolves in a combination of smooth, continuous flow alternating with abrupt, larger-scale atomic reordering, where the abrupt reordering processes continuously increase in size. Finally, shear bands form that cover the entire width of the pillar, which ultimately leads to its collapse. 

Abstract

From uncharted caves to immersive performance spaces, robotics is increasingly called upon to operate in environments that defy traditional engineering assumptions. This keynote explores the parallel challenges and unexpected synergies between designing robots for space exploration and artistic expression. Through the lens of two projects—CAVERNAUTE, a foldable airship built for subterranean missions and performative storytelling, and ARIES, a spherical robot navigating rugged, GPS-denied environments—we reflect on how each domain pushes the limits of structure, autonomy, and human-robot interaction. Both demand not only technical ingenuity but also adaptability, resilience, and imagination. By bridging these seemingly disparate worlds, we uncover how poetic constraints can drive functional breakthroughs, and how the rigor of aerospace inspires novel forms of expressive motion. 

Abstract

Mechanical drivetrains – whether in rotorcraft or wind turbines – pose persistent challenges for dynamics modeling due to nonlinearities, multi-scale behavior, and evolving performance demands.  This talk explores vibration modeling across two distinct but mechanically linked systems: a helicopter tail rotor driveline with friction-induced impacts, and a wind turbine blade-rotor system with complex aeroelastic dynamics.  In the first part, we present a semi-analytical approach to model the nonlinear vibratory response of a tail rotor driveline incorporating a dry friction damper. Through this framework, parametric insights are obtained, enabling efficient optimization for vibration mitigation and robustness.  The method balances analytical tractability with real-system complexity.  In the contrast, the second part transitions to a hybrid modeling paradigm applied to wind turbine systems. Here, high-order structural dynamics are captured using a data-driven approach informed by physical priors, enabling refined predictions without sacrificing computational feasibility.  Together, these case studies illustrate a continuum of modeling strategies – ranging from foundational analytical techniques to modern data-enhanced framework – each chosen to match system characterises and design objectives. I will end the presentation with our recent development on digital twins aiming for both predictability and adaptability across a system’s lifecycle.  

Abstract

Our research focuses on the development of high-productivity additive manufacturing (AM) processes through several R&D projects in collaboration with our aerospace industrial partners located in Canada and in France. We have developed expertise in the design of advanced AM processes (see Figure 1) that enable large-scale non-planar printing of various polymer-based composites mainly for aerospace, but also for biomedical and energy-harvesting applications. One of our unique AM processes involves a six-axis robotic arm on which various types of AM printheads can be installed. This infrastructure enabled the rapid nonplanar multinozzle direct deposition of thermosetting abradable materials for sound absorption of aircraft engines. For the printing of thermoplastics, we integrated the prevalent Fused Filament Fabrication (FFF) process into the same 6-axis robotic platform for non-planar printing of geometrically-optimized sandwich structures using high-temperature-resistant thermoplastic composites such as carbon fiber-reinforced polyetherimide (PEI) and polyetheretherketone (PEEK). Our very recent efforts are focused on the development of a high-throughput AM process based on Fused Granulate Fabrication (FGF) using a pellet-extrusion printhead. Our experimental works on the manufacturing side are supported by numerical simulations. For example, we have created finite element models with element activation based on the manufacturing G-code instructions to predict the heat exchanges during the printing process. In addition, the phase-field modeling approach is used for the crack initiation and propagation predictions within 3D printed composites. We are also investigating the circular economy of materials in the FFF and FGF processes. Our preliminary results are providing comprehensive insights into the sustainability of fiber-reinforced thermoplastic composites for future aerospace applications. 

Abstract

The growing demand for increased flexibility in modern power systems poses a significant challenge to the safe operation of the hydropower asset. Extended operating ranges and frequent start-ups and stops, necessary to regulate the power grid, lead to performance degradation and reduce the lifespan of the hydraulic machines. In particular, start-up sequences of hydraulic turbines play a critical role in their structural integrity and long-term performance.

This talk presents a framework based on experimental investigation, deep learning and optimization techniques to minimize damage during start-up procedures for improved longevity of hydraulic machines. Through high-frequency measurements of dynamic loads and stresses in reduced-scale models of Francis and Pelton turbines, we characterize the transient mechanical stresses experienced during start-up and assess their impact on fatigue-induced damage. To predict fatigue life, we develop physics-based models using both stress-life methods and elastic-fracture mechanics, incorporating crack growth analysis. These models are further leveraged through polynomial expansion techniques and deep learning algorithms, enabling accurate damage estimation under varying operational conditions. Finally, we apply constrained optimization—both convex and nonlinear—to refine start-up protocols, minimizing fatigue-induced damage.

Results demonstrate a substantial reduction in fatigue damage, with optimized start-up sequences lowering damage by up to a factor of 15. These findings underscore the potential of physics-informed machine learning and advanced optimization techniques in extending the service life of hydraulic turbines, offering a pathway toward more resilient hydropower operations.

Abstract

Lagrangian dynamics are omnipresent in both natural and industrial flows, from pathogen and sediment transport to ash distribution in volcanic episodes. The multiscale nature of these flows makes them highly complex, posing significant challenges for both the prediction and interpretation of their dynamics. This is particularly relevant to flows involving particle deposition, agglomeration, dispersal, and similar phenomena.  We therefore carried out a series of experiments to examine an inhomogeneous turbulent jet from the perspective of the particles. We investigate the role of temporal scales in the evolution of Lagrangian dynamics and highlight their significance in understanding how turbulence evolves. Based on these insights, we develop a simple model to "mold" inhomogeneous turbulent fields using a stationary, homogeneous signal input—such as data from Direct Numerical Simulations or stochastically modeled trajectories. In the end, this study presents a straightforward technique to accurately predict not only the large-scale dynamics but also to capture the intermittent effects known to be prevalent, and sometimes detrimental, in many turbulent applications. Finally, we propose extensions to this model that are currently being investigated. 

Abstract

Ultrafast lasers have emerged as a powerful tool for advanced manufacturing. Their short pulse duration, high peak power, and high repetition rate enable high-precision processing over large areas while minimizing damage to surrounding material. 

In this talk, I will present recent work from my research group on ultrafast laser-induced material modifications for colour generation, and micromachining across various materials. 
I will demonstrate how laser-generated nanoscale surface structures can produce vivid colours on silver and copper through a complex interplay of surface morphology, chemistry, and plasmonic activation. Similarly, ultrafast lasers were used to tailor the optical response of polymer nanocomposites, generating structural colours within the bulk by activating surface plasmons at embedded nanoparticles. 

Beyond colouration, ultrafast lasers provide precise control over material removal, from precision cuts to the creation of deep grooves and high-aspect-ratio features. We successfully micromachined ultrathin, free-standing silicon nitride (SiN) membranes with sub-micron precision, fabricating patterns that serve as high-Q resonators that rival those produced in cleanroom environments. I will also discuss the challenges involved in machining high aspect ratio features in metals, highlighting the crucial role laser polarization plays in achieving smooth and straight cuts. 

I will conclude by discussing the broader impact of ultrafast laser technologies, particularly their potential applications in material processing to support a more sustainable environment. 

Abstract

Turbulence research has historically concentrated on canonical flows over smooth flat plates with uniform freestream conditions. However, engineering and environmental applications—including flows around hydraulic turbine blades, naval platforms, and riverine systems—involve dynamically complex flows influenced by surface roughness, curvature, permeability, and unsteadiness. Consequently, conventional turbulence models demonstrate limited utility in practical design and analysis. This research aims to incorporate essential physics into predictive models to enable consistent characterization of turbulence across diverse flow complexities. 
 
This presentation first addresses understanding and modeling for rough-walled, equilibrium and non-equilibrium turbulent boundary layers. Through direct and large-eddy simulations (DNS and LES), we demonstrate how wall roughness fundamentally alters turbulence structure under strong spatial and temporal gradients. Data and insights are used to inform improved roughness-unresolved turbulence closures, including linear eddy-viscosity models, which have traditionally struggled to accurately predict flows with arbitrary roughness characteristics and freestream conditions.  
The second segment explores DNS investigations of critical transport processes in riverine systems—natural turbulent flows bounded by rough, permeable substrates. A knowledge gap exists on how sediment grain-scale dynamics influence multiscale hydrologic processes. We conducted pore-resolved simulations of idealized configurations and show that sediment roughness—frequently neglected in existing predictive frameworks—serves as an important driver of transport in nature. Pore-scale dynamics can significantly influence those at large scales. 

Abstract

Battery technology plays a pivotal role in achieving a decarbonized future by enabling renewable energy integration, ensuring grid stability, and advancing electrified transportation. Despite significant progress, challenges remain in enhancing the energy density, safety, and sustainability of batteries. Due to their high theoretical capacity (10 times that of commercial graphite anodes in Li-ion batteries), lithium (Li) metal anodes represent a promising solution. However, the commercialization of Li-metal batteries is hindered by Li dendrite formation, which degrades performance and poses safety risks. To address this challenge, we developed a series of cost-effective electrolyte additive strategies to prevent dendrite growth while maintaining compatibility with existing production processes. Further, by employing advanced techniques such as synchrotron-based X-ray absorption spectroscopy and microscopy, we demonstrate a novel interface chemistry that enables safer and more efficient lithium batteries. In parallel, we are exploring alternative battery technologies beyond Li, such as zinc (Zn) and aluminum (Al) batteries, which offer improved sustainability and resource efficiency. Several representative works will be presented, addressing critical issues such as battery material design, component development, and cell assembly. We will cover liquid batteries, flow batteries, and all-solid-state batteries. Finally, we highlight key challenges that remain, including safety management, battery recycling, and the broader implications for supporting the energy transition.