Publications

Rock salt, owing to its viscoplastic behavior and structural integrity under high pressure, is a promising candidate for safe and large-scale underground energy storage. This study presents a comprehensive numerical framework for modeling the viscoplastic deformation of rock salt, accounting for both intragranular and grain boundary (GB) deformation mechanisms. Intragranular deformation is modeled using a crystal plasticity approach governed by a power-law relation, capturing the activity of crystallographic slip systems. Concurrently, a cohesive zone model (CZM) is introduced to simulate grain boundary sliding (GBS) and opening via a rate-dependent traction–separation law. This modeling strategy enables a detailed analysis of the coupled interplay between crystal plasticity and intergranular decohesion phenomena.

New standards are being introduced to eliminate toxic elements in materials. For instance, copper alloys should no longer contain lead, although this makes them more challenging to machine. Additionally, for environmental reasons, it is crucial to eliminate cutting oils. To address these two challenges, cryogenic cooling during machining can be considered. However, it is first essential to understand the precise mechanical response of the material at low temperatures. This study conducts compression tests on copper across a wide temperature range, from cryogenic temperatures (liquid nitrogen, LN2) to 700°C, and at strain rates from 0.01/s to 10/s. The microstructure of deformed test samples is also characterized by electron back-scattered diffraction (EBSD) to compare the different plastic deformation characteristics under low and high temperature. The stress-strain curves are fitted with Johnson-Cook (JC) model, which is then implemented into the finite element simulation of the compression process. The results indicate that the JC model with the fitted parameters is not precise enough in terms of modelling very low temperature dynamic response of copper alloy, thus is not proper for the simulation of cryogenic cooling assisted cutting. This is because different characteristics of strain hardening behavior is discovered under LN2 atmosphere temperature and ordinary cutting temperature, which is further induced by a transition of plastic deformation mechanism with increased temperature. Therefore, a new constitutive law is proposed considering deformation mechanism at both traditional cutting temperature and cryogenic conditions. The results indicate that the new model has a better fitting of experimental curves than JC model. This study is helpful for the understanding of low temperature copper deformation behavior and new constitutive model exploitation oriented to cryogenic cooling assisted cutting.

Abstract. In machining industry, there is a growing interest in cryogenic cooling techniques, because of their environmental benefits, including reduced toxicity, safer operation, and lower environmental impact compared to conventional cutting fluids. The titanium alloy Ti6Al4V, which is commonly used in aerospace, automotive and biomedical industries, presents low machinability and often requires abundant use of cutting fluids to inhibit tool wear. This study investigates the machinability of Ti6Al4V, comparing conventional lubrication (water-oil emulsion) with two cryogenic fluids: liquid nitrogen (LN2) and liquid carbon dioxide (LCO2). Longitudinal turning tests were conducted and tool life, wear mechanisms, and cutting forces were evaluated for each lubrication condition. The tool life provided by emulsion, LN2 and Vc were 8.2 min, 17.7 min and 9.9 min, respectively. Adhesion was identified as the predominant wear mechanism across all conditions. Overall, the results suggest that the cryogenic coolants can effectively increase tool life and reduce cutting forces in comparison with conventional lubrication, however, further optimizations of the delivery system of the cryogenic coolants are still necessary.

Abstract. Bulk metallic glasses (BMGs), unlike crystalline alloys, exhibit significantly enhanced plastic deformation when tested at cryogenic temperatures. This enhanced plasticity is primarily characterized by the slowed propagation of shear bands and the formation of multiple shear bands, which play a crucial role in the material's behavior at low temperatures. Due to their amorphous nature, BMGs are prone to catastrophic fractures once shear band nucleation and propagation occur, a behavior distinct from that of crystalline materials. However, the underlying mechanisms of BMG failure and the effect of strain rate remain controversial. This study investigates the mechanical behavior of a Zr-based BMG under cryogenic conditions. Compression tests were conducted at room temperature and -180°C, using liquid nitrogen, across a range of strain rates. The results show that, at cryogenic temperatures, ductility increases, though it remains relatively low, leaving uncertain its impact on machinability. Notably, larger stress drops were observed at ambient temperature, likely linked to shear band formation. Additionally, the study identified two distinct fracture modes during dynamic tests, warranting further investigation. This research provides valuable insights into the behavior of BMGs under cryogenic conditions and their machinability.

High deformation manufacturing processes, such as forming and machining, are complex physical phenomena involving severe thermomechanical and chemical loads. Traditional industrial-scale empirical methods involve high tooling and preparation costs and long lead times before manufacturing, which is undesirable in modern industry. The use of predictive models helps to reduce these weaknesses. Finite Element Method (FEM) models are a useful, reliable and cost-effective tool for studying manufacturing processes. Several approaches have been used to model these processes with the FEM. The Lagrangian formulation with implicit time integration scheme is the most widely used because of its reliability. However, element distortion due to severe plastic deformation and chip separation, in the case of machining, has always been a major concern of this approach. This paper therefore presents the development of a customizable and optimized FEM model with Lagrangian formulation and remeshing technique that solve the mesh distortion problem. The model was developed using the general-purpose software Abaqus/Standard commanded by Python scripting. The remeshing criterion is based on the relative plastic deformation at each load increment controlled by two subroutines working together UVARM+URDFIL. A forming problem was selected to optimize the mesh size and number of remeshings with the goal of reducing the simulation time. Then, the proposed model was compared to Lagrangian models without remeshing and Arbitrary Lagrangian-Eulerian (ALE) formulation. The model was also experimentally validated demonstrating improvements over other approaches and formulations, and laying the foundation for further development, such as applying it to the machining process.

The need to reduce fuel consumption and emissions is driving advances in aeroengine performance. Efficiency gains are limited by the capacity of the turbine material to withstand the high thermomechanical loads of the combustion process. Nickel-based alloy Udimet 720Li has emerged as a promising alternative to the most widely used Inconel 718 for critical aeroengine components. Nonetheless, its material properties under industry-relevant conditions remain understudied, hindering industrial implementation. Furthermore, discrepancies in the methodology for applying adiabatic heating correction in thermomechanical tests on nickel-based alloys prevent comparability of studies and alloys. This paper presents the thermophysical and thermomechanical properties of forged and heat-treated Udimet 720Li to enable advanced aeroengine design and manufacture. A novel adiabatic heating correction procedure is also proposed for thermomechanical tests. Thermophysical properties (specific heat, density, diffusivity, thermal expansion, and conductivity) were characterised for temperatures 20–1200 °C. Thermomechanical properties were obtained for temperatures 20–1100 °C and strain rates 0.01–100 s-1 with cylinder compression tests. The results show that Udimet 720Li exhibits higher thermomechanical properties than Inconel 718 at elevated temperatures and can withstand greater in-service temperatures (8–23 %) due to the higher γ’ strengthening phase content which remains stable up to 760 °C.

The 2020s represent both the digital decade and the pivotal period in the fulfillment of long-standing commitments made by public, private, and institutional actors in favor of sustainable development. In the manufacturing context, Product Lifecycle Management (PLM) systems are used during the design phase to reduce product environmental footprint. However, only a few studies have thoroughly identified the environmental impacts associated with these technological solutions. This study proposes a sensitivity analysis of five environmental impact categories associated with two PLM system architectures and three mitigation scenarios. To this end, we use an engineering school as a representative PLM system case study, relying on the Life Cycle Assessment (LCA) methodology and leveraging specialized tools that enable the execution and comparative analysis of multiple LCA scenarios. Our results consistently identify the manufacturing and usage phases of PLM system users’ equipment as the main contributors of the PLM system to climate change, acidification, and the depletion of abiotic mineral and metal resources. End-of-life contributes significantly to particulate matter impact, and usage phase, in a nuclear mix country, to ionizing radiation. The policy of purchasing and reselling reconditioned users’ equipment is clearly identified as a key lever for reducing the magnitude of these five environmental impacts.

Patient-specific models have increasingly gained significance in medical and research domains. In the context of hemodynamic studies, computational fluid dynamics emerges as a highly innovative and promising approach. We propose to augment these computational studies with cell-based experiments in individualized artery geometries using personalized scaffolds and vascular cell experiments. Previous research has demonstrated that the development of Sickle Cell Disease (SCD)-Related Vasculopathy is dependent on personal geometries and flow characteristics of the carotid artery. This fact leaves conventional animal experiments unsuitable for gaining patient-specific insights into cellular signaling, as they cannot replicate the personalized geometry. These personalized dynamics of cellular signaling may further impact disease progression, yet remains unclear. This paper presents a six-step methodology for creating personalized large artery scaffolds, focusing on high-precision models that yield biologically interpretable patient-specific results. The methodology outlines the creation of personalized large artery models via Additive Manufacturing suitably for supporting cell culture and other cellular experiments. Additionally, it discusses how different Computer-Aided-Design (CAD) construction modes can be used to obtain high-precision personalized models, while simplifying model reconfigurations and facilitating adjustments to general designs such as system connections to bioreactors, fluidic systems and visualization tools. A proposal for quality control measures to ensure geometric congruence for biological relevance of the results is added. This innovative, interdisciplinary approach appears promising for gaining patient-specific insights into pathophysiology, highlighting the importance of personalized medicine for understanding complex diseases,

Mental workload overload is a major cause of human error in industrial tasks such as maintenance. Human errors can compromise not only system safety but also lead to high social and economic costs, reduce equipment productivity, and cause incidents, accidents, and fatalities. To this day, we do not have an adequate assessment of mental workload in maintenance, which would help design maintenance processes more effectively by incorporating this crucial aspect. The objective of this study is to determine the ability of our indicators to measure mental workload during a disassembly and assembly task in a laboratory condition. Thirty-six participants performed a disassembly and assembly task under two different mental workload conditions. Subjective measures (NASA-TLX), performance metrics (number of errors), and cardiovascular data (heart rate, heart rate variability, and breathing rate) were analyzed. We observed a higher number of errors and elevated NASA-TLX scores in the high mental workload condition. Regarding cardiovascular data, interesting trends in the temporal domain were observed despite mostly non-significant results. Although conducted in a laboratory, this multimodal mental workload measurement method is promising for diagnosing and understanding operators' cognitive behavior, and deserves validation in real-world maintenance conditions.

In Robotized Incremental Sheet Forming (ISF), achieving precise geometrical accuracy is a challenging task due to trajectory tool center point (TCP) position errors at the forming tool attached to the robot’s end-effector. These errors primarily arise from external disturbance forces and torques generated during the interaction between the forming tool and the elastic metal sheet. While jointtorque space controllers can mitigate reaction forces and torques through dynamic modeling, jointspace control has inherent limitations, particularly for industrial high-load robots like the ABB IRB 8700. To overcome these challenges, thiswork implements an external force/torque (F/T) compensator in task-space using a deep neural network. The network predicts trajectory errors induced by reaction forces and torques measured via a 6-axis F/T sensor. Additionally, the forming tool’s trajectory is precisely monitored using a laser tracker, which serves as a feedback mechanism in a closed-loop task-space error-tracking controller. This controller detects and corrects trajectory deviations in real time. By integrating the F/T compensator and the task-space error-tracking controller, the proposed approach effectively compensates for reaction forces and torques while addressing additional errors introduced by other process-related factors. This integration results in significantly enhanced accuracy in robotic incremental forming processes.