École de Technologie Supérieure
  • Montréal, Quebec, Canada
Recent publications
Ecomaterials used in traditional construction are experiencing renewed interest for their low environmental impact. However, the lack of reference values for the hygrothermal behaviour of some composite ecomaterials with a low carbon footprint prevents the overall analysis of the structures of buildings designed with these materials. The wood-clay construction system is an ecological and sustainable building system. These materials have great potential for applications in places where housing needs are high, in rural areas of Africa, and have been used for hundreds of years in Europe. The plant fibres improves the hygrothermal, mechanical and weather resistance performance of clay materials. This study determines the water content absorbed by the wheat and corn stalk fibres that will allow the water/clay ratio to be adjusted. For the characterization of red and white clay, the results obtained by the pycnometer method show that the bulk density of the clay is 2.80 and 2.73 with an absolute density of 2.79 g/ml and 2.72 g/ml. The results of the characterization of wheat and corn fibres show that they have the capacity to absorb more than 200% and 120% water by weight in only 25 min respectively at 23℃. The water absorption of fibres increases with increasing temperature. This increase contributes to the improvement of the hygrothermal performance of the materials by the restitution of the absorbed humidity, providing a very good feeling of comfort. Samples formulated with 0% to 3% wheat fibre have shown that the addition of fibre reduces the shrinkage of clay materials by 6.35 to 1.53%.
This paper presents a grid-integrated single phase solar photovoltaic (PV) system (GISPSPS) with its modeling, design and control. The GISPSPS consists of a single switch based high gain boost converter (HGBC) and full bridge voltage source converter (FBVSC). The HGBC, boost the low PV panel voltage and extracts the optimum PV power. The HGBC allows high voltage conversion ratio and possesses less voltage stresses on power devices. The optimum PV power is extracted via a sliding mode control (SMC) strategy that generates the switching signal for the switch of HGBC. The FBVSC delivers PV power to the single phase utility grid, as well as load connected at point of interfacing (POI). A fifth order generalized integrator (FiOGI) is developed for FBVSC control to ensure harmonic suppression and DC offset rejection capability during extraction of fundamental grid voltage. Experimental validation of proposed GISPSPS and its control is also verified.
Introduction There is a growing need for small-diameter (<6 mm) off-the-shelf synthetic vascular conduits for different surgical bypass procedures, with actual synthetic conduits showing unacceptable thrombosis rates. The goal of this study was to build vascular grafts with better compliance than standard synthetic conduits and with an inner layer stimulating endothelialization while remaining antithrombogenic. Methods Tubular vascular conduits made of a scaffold of polyurethane/polycaprolactone combined with a bioactive coating based on chondroitin sulfate (CS) were created using electrospinning and plasma polymerization. In vitro testing followed by a comparative in vivo trial in a sheep model as bilateral carotid bypasses was performed to assess the conduits’ performance compared to the actual standard. Results In vitro, the novel small-diameter (5 mm) electrospun vascular grafts coated with chondroitin sulfate (CS) showed 10 times more compliance compared to commercial expanded polytetrafluoroethylene (ePTFE) conduits while maintaining adequate suturability, burst pressure profiles, and structural stability over time. The subsequent in vivo trial was terminated after electrospun vascular grafts coated with CS showed to be inferior compared to their expanded polytetrafluoroethylene counterparts. Conclusions The inability of the experimental conduits to perform well in vivo despite promising in vitro results may be related to the low porosity of the grafts and the lack of rapid endothelialization despite the presence of the CS coating. Further research is warranted to explore ways to improve electrospun polyurethane/polycaprolactone scaffold in order to make it prone to transmural endothelialization while being resistant to strenuous conditions.
With the rapid development of electric vehicles, the disposal of retired lithium batteries is a grand challenge for the waste management based on reliability, efficiency and sustainability criteria. Majority of studies in the literature review, have focused on the minimization of environmental pollution while maximizing economic profits. However, the literature is still in favor of different reliability, efficiency and sustainability criteria which are urgent and essential for the recycling of spent lithium-ion batteries (SLIBs). To this end, this study does a comprehensive review on existing methods, key issues, and technical challenges in the field of SLIBs recycling. The significant contributions of this work are to systematically explain the pretreatment process, leaching process, chemical purification process, and industrial applications. Finally, future research opportunities and managerial insights in the field of SLIBs recycling are discussed while introducing smart, intelligent and sustainable recycling of SLIBs.
Industry 4.0 is a central strategy to strengthen the competitiveness of the manufacturing sector over the next years. Nevertheless, there is a lack of common understanding of Industry 4.0 and tools to help companies’ transformation to Industry 4.0, especially for small and medium-sized enterprises (SMEs). To address these research gaps, this study proposes a framework to characterise and evaluate Industry 4.0 scenarios to aid companies’ transition towards Industry 4.0. For this, a design science (multi-methodological) approach is adopted, including an Industry 4.0 use case survey, modelling and simulation and two proof-of-concept cases developed in collaboration with a Canadian college centre for technology transfer. The results indicate that the proposed framework can help companies identify Industry 4.0 scenarios more intuitively to assist project conception, portfolio selection and planning during Industry 4.0 roadmap development. Finally, the results of this study suggest that Industry 4.0 can be implemented incrementally while companies increase their digital capabilities and maturity.
Seasonal snowpack deeply influences the distribution of meltwater among watercourses and groundwater. During rain-on-snow (ROS) events, for instance, the structure and properties of the different ice and snow layers dictate the quantity of water flowing out of the snowpack, increasing the risk of flooding and ice jams. With ongoing climate change, a better understanding of the processes and internal properties influencing snowpack outflows is needed to predict the hydrological consequences as mild episodes and ROS events’ frequency increases. This study aims to develop a multi-method approach to monitor the key snowpack properties in a non-mountainous environment in a repetitive and non-destructive way. Snowpack evolution was evaluated using a combination of drone-based GPR, photogrammetry surveys and time domain reflectometry (TDR) measurements, tested during the winter of 2020–2021 at the Sainte-Marthe experimental watershed, Quebec, Canada. The experimental watershed is equipped with state-of-the-art automatic weather stations that, together with weekly snow pit measurements, serve as a reference for the multi-method monitoring approach. Drone surveys conducted on a weekly basis are used to generate georeferenced snow depth, relative density, snow water equivalent and average liquid water content maps. In between site visits, snowpack properties are monitored using TDR probes. Despite some limitations, the results show that the approach is very promising in assessing the spatiotemporal evolution of the key hydrological characteristics of the snowpack. Among others, results showed the prevalence of preferential pathways at the early stage of the ablation period, the difference in hydrological reaction to a ROS event between flat and sloped sections of the study area and the hydrological influence of solar radiation at the late stage of the ablation period.
We study a new variant of the well-studied vehicle routing problem with time windows (VRPTW), called the fragility-constrained VRPTW, which assumes that (1) the capacity of a vehicle is organized in multiple identical stacks; (2) all items picked up at a customer are either “fragile” or not; (3) no nonfragile items can be put on top of a fragile item (the fragility constraint); and (4) no en route load rearrangement is possible. We first characterize the feasibility of a route with respect to this fragility constraint. Then, to solve this new problem, we develop an exact branch-price-and-cut (BPC) algorithm that includes a labeling algorithm exploiting this feasibility characterization to efficiently generate feasible routes. This algorithm is benchmarked against another BPC algorithm that deals with the fragility constraint in the column generation master problem through infeasible path cuts. Our computational results show that the former BPC algorithm clearly outperforms the latter in terms of computational time and that the fragility constraint has a greater impact on the optimal solution cost (compared with that of the VRPTW) when vehicle capacity decreases, stack height increases, and for a more balanced mix of customers with fragile and nonfragile items.
We present results of atomic-force-microscopy-based friction measurements on Re-doped molybdenum disulfide (MoS2). In stark contrast to the widespread observation of decreasing friction with increasing number of layers on two-dimensional (2D) materials, friction on Re-doped MoS2 exhibits an anomalous, i.e., inverse dependence on the number of layers. Raman spectroscopy measurements combined with ab initio calculations reveal signatures of Re intercalation. Calculations suggest an increase in out-of-plane stiffness that inversely correlates with the number of layers as the physical mechanism behind this remarkable observation, revealing a distinctive regime of puckering for 2D materials.
This paper proposes Boost Packed E-Cell (BPEC) as an affordable Compact Multilevel Converter (CMLC) for the power quality ancillary services. The BPEC is a transformerless bidirectional CMLC topology and can generate symmetrical and asymmetrical multilevel voltage waveforms with 5-to-11-level resolution using only three low-voltage dc capacitors and eight power switches. Thanks to the serial expansion of the two dc capacitors, BPEC has two dc-links, which means two voltage sensors are enough to control three dc capacitors. Despite other CMLCs, BPEC does not need a fault detector and inherently generates a symmetrical 5-level or an asymmetrical 7-level voltage waveform in the event of a fault of the middle switches or their gate drivers. As a case study, a single-phase Compact Active Power Filter (CAPF) is designed in this paper based on the BPEC to compensate for harmonics and reactive power caused by unknown non/linear loads, simultaneously. Finite control set predictive control strategy is also adopted based on the switched model of the power system containing the grid, unknown non/linear loads, and the BPEC to address the grid power quality concerns. The experiments performed by a prototype including the BPEC power board, MicroLabBox, OPAL-RT OP8662, and Chroma 61086 verify the merits of the proposed CAPF in practice.
Carbon fiber-reinforced polymer (CFRP) composite materials are massively used since the last decades in many contemporary applications, especially in aerospace for their strength to density and stiffness to density ratios which are higher than alloys. On the other hand, CFRP are known to be difficult to machine compared to metals due to their heterogeneous and anisotropic structure. Common damages like delamination, fiber loosening and pull out, uncut fibers, and mechanical and thermal damages to the epoxy matrix are observed after machining. This research studies the effect of graphene particles addition in epoxy matrix of CFRP on the cutting temperature, in a global objective of improving the machinability and cutting tool life. Thereby, four modified resin plates (0%wt, 0.25%wt, 3%wt, and 10%wt of graphene) without carbon fibers (nanocomposite plates only) were first molded. Next, three CFRP laminates with different percentages of graphene (0%wt, 0.25%wt, and 3%wt) were manufactured using a combination of vacuum bagging and hydraulic pressing in order to guarantee a good fillers’ distribution within the composite plates and a consistent fiber volume fraction. The trimming experiments were performed using a polycrystalline diamond (PCD) tool which was selected for its well-known machining performance. As expected, the tool wear was nonexistent on nanocomposites. For CFRP plates, the tool wear remained in its break-in zone throughout the experiment (final Vb \(\approx 0.051\ll 0.3 \mathrm{mm}\) for a final length cut of 4.5 m). The cutting tool’s temperature increases with graphene concentration for both nanocomposites and CFRP samples. However, the temperature increase of CFRP plates was reduced by 30% with a graphene concentration of 3%wt. The feed forces were also greatly reduced (up to 43%) with graphene when machining CFRP.
Mobile applications (apps) are developed quickly and evolve continuously. Each development iteration may introduce poor design choices, and therefore produce code smells. Code smells complexify source code and may impede the evolution and performance of mobile apps. In addition to common object-oriented code smells, mobile apps have their own code smells because of their limitations and constraints on resources like memory, performance and energy consumption. Some of these mobile-specific smells are behavioural because they describe an inappropriate behaviour that may negatively impact software quality. Many tools exist to detect code smells in mobile apps, based specifically on static analysis techniques. In this paper, we are especially interested in two tools: Paprika and aDoctor. Both tools use representative techniques from the literature and contain behavioural code smells. We analyse the effectiveness of behavioural code smells detection in practice within the tools of concern by performing an empirical study of code smells detected in apps. This empirical study aims to answer two research questions. First, are the detection tools effective in detecting behavioural code smells? Second, are the behavioural code smells detected by the tools consistent with their original literal definition? We emphasise the limitations of detection using only static techniques and the lessons learned from our empirical study. This study shows that established static analysis methods deemed to be effective for code smells detection are inadequate for behavioural mobile code smells detection.
This paper aims to present a new methodology to model the aerodynamic coefficients and predict the aircraft dynamics under stall conditions, including the hysteresis cycle, using neural networks. The aerodynamic coefficients variations required for the identification process were estimated from flight data collected during different stall maneuvers. Then, a level-D-qualified Bombardier CRJ-700 virtual research equipment simulator (VRESIM) developed by CAE, Inc. and Bombardier was used to gather flight data in both linear and nonlinear stall phases. According to the Federal Aviation Administration (FAA), level D is the highest qualification level for flight dynamics and propulsion models. Multilayer perceptron (MLP) and recurrent neural networks were trained for the aerodynamic coefficients learning and their correlation with flight parameters. A new methodology for tuning the neural network parameters, such as the optimal number of layers and neurons, was developed. The resulting models were validated by comparing predicted flight data with experimental data obtained from the level D Bombardier CRJ-700 VRESIM by considering the same pilot inputs. The models developed using the proposed methodology were able to predict the CRJ-700 flight dynamics in both static and dynamic stall conditions, with very good precision, within the tolerances of the FAA.
A method for structural analysis of thin-walled composite beams like wind turbine blades is presented. This method is based on the Nonhomogeneous Anisotropic Beam Section Analysis (NABSA) which consists in discretizing the beam cross section using finite elements. The proposed implementation uses 3-node line cross-sectional finite elements with nodes having rotational degrees of freedom to describe the cross-sectional warping displacements. Solutions obtained using this approach were verified against the corresponding analytical or numerical solutions. Agreement was very good to excellent for the computation of cross-sectional properties and distribution of stresses, strains and warping displacements for a broad range of possible composite beam behaviors including geometric and material couplings, open sections, multicell sections, and arbitrary laminates. For thin-walled layered structures, the proposed method provides models with fewer degrees of freedom than equivalent models based on a two-dimensional discretization of cross sections using triangular or quadrilateral elements such as conventional NABSA or VABS which suggests that computation time could be reduced.
In semi-supervised medical image segmentation, the limited amount of labeled data available for training is often insufficient to learn the variability and complexity of target regions. To overcome these challenges, we propose a novel framework based on cross-model pseudo-supervision that generates anatomically plausible predictions using shape awareness and local context constraints. Our framework consists of two parallel networks, a shape-aware network and a shape-agnostic network, which provide pseudo-labels to each other for using unlabeled data effectively. The shape-aware network implicitly captures information on the shape of target regions by adding the prediction of the other network as input. On the other hand, the shape-agnostic network leverages Monte-Carlo dropout uncertainty estimation to generate reliable pseudo-labels to the other network. The proposed framework also comprises a new loss function that enables the network to learn the local context of the segmentation, thus improving the overall segmentation accuracy. Experiments on two publicly-available datasets show that our method outperforms state-of-the-art approaches for semi-supervised segmentation and better preserves anatomical morphology compared to these approaches. Code is available at https://github.com/igip-liu/SLC-Net.
This research aims to determine if the observed improvements using polyethylene (PE) waste in asphalt binder translate into better performance at the asphalt mixture scale in the laboratory environment while overcoming the stability and homogeneity issues experienced at the binder level. This is accomplished through a round-robin multinational experimental program covering four continents, with the active participation of eleven laboratories within the RILEM TC 279-WMR. PE modified AC16 mixtures were prepared employing the dry process using local materials with the PE waste provided by one source. Various mechanical tests were performed to investigate the compactability, strength, moisture sensitivity, stiffness and permanent deformation. Compared to the control mixtures, the following observations were made for PE modified mixtures: easier to compact, lower time dependence of stiffness, higher elastic behavior, lower creep rate, and higher creep modulus. Furthermore, cyclic compression test results showed that the resistance to permanent deformation is improved when using PE in asphalt mixtures, whereas the wheel tracking tests showed relatively similar or better results when 1.5% PE was added to the control mixture. The wheel tracking test results in water showed an increase in deformation with increasing PE content. The interlaboratory investigation showed that the use of PE as a performance-enhancing additive in asphalt pavements is a viable, environmentally friendly option for recycling waste plastic and could potentially reduce the use of polymer additives in asphalt.
Despite rising awareness concerning climate change, global anthropic impacts on the environment are forecasted to increase in the overcoming years, exceeding our planet’s ecological limits. The accelerating pace of climate degradation calls for a quick and efficient response from our societies, should we have a chance to limit the impacts of global warming. Being main nodes of over-consumption and pollution, thus having a high potential for footprint reduction, cities are crucial actors for climate mitigation. Hence, to successfully achieve a transition towards real sustainability, knowledge transfer needs to happen from the cities that are aiming towards life-respecting planetary boundaries to other urban regions worldwide. Although gaining momentum in the literature, a life respecting Earth’s Carrying Capacity (ECC) is not yet explicitly nor widely set as the ultimate goal for cities wanting to realistically face climate change. This article’s purpose is to reflect on the identification of cities actively aiming for ECC and point out the various obstacles to this goal. A misrepresentation of cities’ impact, both induced by misused sustainability terms and incomplete assessment methodology, is found to be hindering cities from reducing their footprint with the efforts needed to adequately face climate change. To that extent, it is crucial that ECC becomes a wider used target for cities, and that compliant assessment methods along with more holistic indicators are used to evaluate and monitor their progress. Finally, other technical issues regarding the incompleteness of standards, accessibility, and representativeness of qualitative data must be addressed.
In the last decades, titania (or TiO2) particles played a crucial role in the development of photo-catalysis and better environmentally-friendly energy-harvesting techniques. In this work, we engineer a new generation of TiO2 particles rich in oxygen vacancies using a modified sol–gel synthesis. By design, these vacancy-rich particles efficiently absorb visible light to allow carefully-controlled light-induced conversion to the anatase or rutile crystalline phases. FTIR and micro-Raman spectroscopy reveal the formation of oxygen vacancies during conversion and explain this unique laser-assisted crystallization mechanism. We achieve low-energy laser-assisted crystallization in ambient environment using a modified filament 3D printer equipped with a low-power laser printhead. Since the established high-temperature treatment necessary to convert to crystalline TiO2 is ill-suited to additive manufacturing platforms, this work removes a major fundamental hurdle and opens whole new vistas of possibilities towards the additive manufacturing of ceramics, including carefully-engineered crystalline TiO2 substrates with potential applications for new and better photo-catalysis, fuel cells and energy-harvesting technologies.
Flexible printed sensors are essential components for modern Internet of Things applications. They may twist and bend to fit any shape or surface. New potential applications emerge as these sensors’ sophistication and sensing efficiency improve. In this study, a printed sensor is prepared from indium oxide nanoparticles (In2O3 NPs)‐based nanocomposite for hydrogen sulfide (H2S) gas detection at ambient conditions. The as‐fabricated sensor has excellent capabilities, including sensitivity and selectivity to low gas concentrations than 100 ppb (<100 ppb), anti‐humid property up to relative humidity (RH) ≈ 100%, high chemical stability in severe environments, good mechanical flexibility up to 50 bending cycles at 30° bending angle, and good thermomechanical stability between ‐40 °C ‐ 40 °C. Moreover, the sensor detects the low concentrations of H2S gas produced during the spoilage of organosulfur‐rich food (beef and fish) while remaining insensitive to humidity changes up to RH ≈ 100%, resulting in the fist‐of‐its‐type chemiresistive sensor for food packaging application. The sensors’ response to H2S gas is based on the contribution of the physical and chemical sensing mechanisms, which rely on the H2S molecules’ reactions on the sensor's surface with the adsorbed oxygen molecules and the sensing materials (copper acetate (CuAc) and In2O3 NPs), respectively. This study presents a printed indium oxide nanoparticles‐based sensor for hydrogen sulfide (H2S) gas detection at ambient conditions. The as‐fabricated sensor demonstrates excellent capabilities, making it an excellent digitalized tool for monitoring the spoilage of organosulfur‐rich food (such as red and white meat). This suggests the sensor's potential use in food packaging applications with high commercialization potential.
Flax fiber-reinforced polymer composites are an interesting alternative to synthetic fiber-reinforced polymer composites for many engineering applications. When machining flax fiber-reinforced composite materials that are by definition heterogeneous, the matrix and the fibers react differently and hence many sorts of damage may occur such as poor surface roughness, delamination, and fluffing. The novelty of the current work lies in identifying the major factors that affect the quality of the milled surface of composites reinforced with flax fibers and provides recommendations and collaborative solutions to the composite machining community. In this study, the impact of cutting conditions (cutting speed, feed rate, and fiber orientation) on the cutting forces and surface roughness during milling of the flax/epoxy composite is investigated. For this purpose, slotting tests are performed on flax fiber-reinforced polymer plates using a carbide end mill tool based on a full factorial design of experiment. Furthermore, a randomization in the order in which experimental runs are done is used to reduce bias by balancing the effect of uncontrolled variables that have not been accounted for in the experimental design. It is concluded that the feed rate has the most influence on the cutting forces and roughness parameters. Moreover, the fibers orientation also has a significant effect on the outputs, and the cutting speed has less effect but it remains significant.
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Vincent Levesque
  • Département de génie logiciel et des technologies de l'information
Borhen Louhichi
  • Laboratoire d’ingénierie des produits, procédés et systèmes (LIPPS)
Almur A S Rabih
  • Département de génie électrique
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