Publications

This study proposes a methodology for examining the relationship between environmental thermal conditions and occupant's perceived thermal comfort evaluation. Therefore, their psychological adaptation was examined to quantify and incorporate it in thermal comfort evaluations. To achieve the closure of the model's system of equations, experiments are carried out in which subjects are exposed to various thermal conditions in an enclosed space that simulates an office indoor environment; thermal measurements and perceived data are collected. Thus, the study aims to evaluate the adaptive factor that causes the difference between the physiological evaluation and the subjects’ actual thermal perception. This adaptive factor is linked to the physical stimuli experienced owing to the thermal environment and the cognitive information within the occupant's memory systems; thus, the closure equation is derived from the outdoor air temperature and indoor operative temperature.

The present paper analyzes separately the effect of the features of the typical AM defects on the fatigue resistance of Ti-6Al-4V alloy. To do so, different defect population in terms of sizes and morphologies were obtained by varying the L-PBF process parameters. The distance of these defects with respect to the surface was also controlled. A uniaxial fatigue testing campaign (R = −1) has then been conducted. The results have showed great influence of the nature of the defect population on the fatigue strength of Ti-6Al-4V alloy, for the case of surface crack initiation. The results have also allowed to quantify the criticality of internal defects with respect to their sizes and showed that the defect morphology has no influence on the fatigue strength for the case of internal crack initiation.

Immersive Digital Twins (IDT) have many advantages for training en-gineering students in the use of industrial machines. Some of the advantages are practical, such as avoiding the need to buy machines that are very expensive to maintain, saving energy and journeys. There are also advantages in terms of learning, since immersion improves performance for certain types of content. In addition, immersive environments now make it possible to integrate intelligent virtual agents, thanks to the development of language models. These new possi-bilities will undoubtedly lead to new forms of teaching in engineering schools. Most of the researches are focused on optimizing course situations. However, there is currently a lack of research regarding their impact on the learners inde-pendent study, and on the role of the teachers in the use of these devices.

It is essential to ensure that the mental workload during a maintenance activity is not too high, in order to protect the integrity of maintenance operators and aviation safety. In particular, anticipating human error, which remains one of the consequences of the variability of the mental workload, leads us to define an appropriate method for measuring the mental workload during the maintenance activity. In the aviation industry and in the frame of mental workload assessment, subjective, objective, and physiological approaches will provide adequate solutions in a context always influenced by multiple constraints. Ultimately, these data will enable us to better anticipate the design of more robust and fault-tolerant systems that ensure the protection of operators' physical and mental integrity.

In this work, experimental tests and numerical simulations are carried out to investigate the buckling behavior and failure modes of auxetic cellular structures and sandwich panels with auxetic cores. Different Poisson's ratios and densities are considered to evaluate the impact of these parameters on the deformation mechanisms under uniaxial compression loading. The numerical analysis is performed using the Riks method, while considering geometric nonlinearity and elastoplastic behavior. The results indicate that negative Poisson's ratio and structure density have a significant influence on the buckling critical stress and the failure mechanisms of cellular structures. Although the inverted honeycomb and the double arrowhead with different Poisson's ratios exhibit similar load capacity, facesheet failure is more pronounced with the conventional inverted honeycomb. This result can be attributed to the dominant effect of the facesheet on the load evolution. The effects of the cell-wall thickness and the facesheet thickness on the buckling load are also discussed based on the finite element model.

Lifting hydrofoils are gaining importance, since they drastically reduce the wetted surface area of a ship, thus decreasing resistance. To attain efficient hydrofoils, the geometries can be obtained from an automated optimisation process. However, hydrofoil simulations are computationally demanding, since fine meshes are needed to accurately capture the pressure field and the boundary layer on the hydrofoil. Simulation-based optimisation can therefore be very expensive. To speed up the fully automated hydrofoil optimisation procedure, we propose a multi-fidelity framework which takes advantage of both an efficient low-fidelity potential flow solver dedicated to hydrofoils and a high-fidelity RANS solver enhanced with adaptive grid refinement and dedicated foil-aligned overset meshes, to attain high accuracy with a limited computational budget. Both solvers are shown to be reliable for automatic simulation, and remarkable correlation between potential-flow and RANS results is obtained. Two different multi-fidelity frameworks are compared for a realistic hydrofoil: only RANS based and potential-RANS based. According to the optimisation results, the drag is able to be reduced by 17% and 8% in these frameworks, within a realistic time frame. Thus, industrial optimisation of hydrofoils appears possible. Finally, critical areas of future improvement regarding the robustness and efficiency of the optimisation procedure are discussed in this study.

Designing automotive Head-Up Displays (HUD) interfaces requires careful consideration of visual guidelines to ensure safety. While specific safety guidelines exist, a general set of visual guidelines has not yet been established. Therefore, this research presents a comprehensive methodology to derive overall visual guidelines designed to project warnings on HUD interfaces. To this end, the present work focused on asking 20 test subjects for driving in various scenarios, while visual stimuli were projected on a specific HUD system, identifying drivers’ behavior patterns and reaction trends. These visual stimuli were based on already tested visual guidelines. The results obtained from this methodology show that it is possible to integrate all previous qualitative and quantitative visual guidelines, allowing for drivers faster reactions and better recognition of warnings. This integration enables determining the most and the least suitable way for presenting information in a specific HUD system concerning identification mistakes and reaction times. Moreover, these findings imply the feasibility of anticipating a driver’s comprehension of warnings in HUD interfaces.

The study of capillary flows in cellulose fibers is important for various applications, including biomass pyrolysis and drying processes. This work investigates the behavior of cotton fibers during capillary impregnation using a dynamic approach. The analysis utilizes the Washburn equation and tensiometric methods to investigate geometric factors, apparent advancing contact angles, surface free energy of cotton fiber, and capillary pressure. The research is carried out in two phases. The first phase focuses on the theoretical application of the Washburn equation in porous cotton fibers, specifically examining capillary wicking behavior within a cylindrical holder. The second phase involves experimental analysis, using three different liquids: n-heptane, water, and glycerol. The surface tension of the liquids was measured, and the capillary impregnation process was characterized through the determination of geometric factors, apparent advancing contact angles, and surface free energy. The geometrical factors of cotton fibers within the sample holder were found to be 10.39 ± 1.28 mm5. The apparent advancing contact angles for water and glycerol were 74.93◦ ± 2.20◦ and 69.55◦ ± 1.83◦, respectively

The industry sector has long been seeking methods to enhance its manufacturing system control, production, and monitoring, while maintaining the quality of its products and reducing costs and time. One method for achieving a more comprehensive understanding of the manufacturing processes is the identification of a corresponding process window (PW). However, there is no globally accepted definition of process window, which is principally used in different manufacturing processes. In some cases, it is combined with operating window or process map concepts. In light of the aforementioned consideration, this article puts forth a definition of process window, drawing upon the various notions and aspects related to the optimal process parameters selection as discussed in the literature. Furthermore, the identification of key controllable process parameters and the criteria to delimit boundaries of desired parts are described as aspects to identify the corresponding process window. Moreover, this paper provides an overview of the techniques used to establish a process window, principally through the application of machine learning techniques (ML) and design of experiments (DOE). Furthermore, the uncertainty intrinsic to the manufacturing process and the methodologies employed to identify the process window are examined. In conclusion, this article emphasises the necessity of transferring these models to new materials or machines, which will require further investigation in future research.

Risk management has always been a trend in manufacturing related literature in the era of zero-defect manufacturing (ZDM). However, a gap still exists to present a holistic viewpoint of the integration for a product and its related processes involved during decision-making in manufacturing industry. The (knowledge-driven) integrated-decision support system indicates the opportunity by integrating the product design and manufacturing processes related risks in a manufacturing industry to make better decisions at the shop foor. It further proposes a direction towards development of a decision support system framework for their respective risks’ identifcation as well as mitigation to enhance the quality, while minimizing time and cost. Over the years, risk identifcation has been considered well but risk mitigation has mostly been overlooked in the published literature. This paper scanned over a thousand papers from renowned journals published between 2005 and 2024. Currently, the evolu tion involved in the advancement of decision support tools for risk management has been reviewed by utilizing systematic literature review methodology. The study also provides a design overview, highlighting its features, pros, and cons of the existing methods which can be used for risk identifcation, prioritization, and mitigation in the development of a dynamic decision support system to aim (data-driven) zero-defect manufacturing (ZDM). Lastly, the paper discusses the current challenges and opportunities to lessen the manufacturing recalls in the industry, followed by phases of the proposed model.