https://popups.uliege.be/esaform21 ESAFORM is an association with the mission to stimulate applied and fundamental research in the field of material forming. Its annual conference, the International ESAFORM Conference on Material Forming, is used to achieve one of the main goals of ESAFORM: to spread scientific and technological information related to material forming within academic and industry. The next conference will be held online on 14-16 April 2021. fr https://popups.uliege.be/esaform21/index.php?id=2151 Auxiliary systems for sheet forming processes are widely used to improve products accuracy and increase tools life. As example, in blanking hydraulic dampers are widely used to reduce shocks and vibrations; nitrogen springs are often integrated in deep drawing tools to correct the ram tilt or to locally increase the blank-holder force, obtaining geometrical features on the stamped blank with one press pass. In this paper, a Magneto-Rheological (MR) semi-active actuator is developed for sheet forming operations and the interaction between MR fluid and electromagnetic field is investigated by Finite Element (FE) analysis. To overcome the limitations of gas springs and hydraulic actuator, the static electromagnetic circuits is reconfigured with respect of conventional MR actuators known in the state-of-the-art. The novel MR actuator has an inner bore where the electric windings are placed, while the narrow gap, in which the active MR fluid flows, is obtained between the inner bore and the cylinder internal surface. The resulting magnetic fields H and induction fields B, as well as the selection of components materials, are studied through the magneto-static FE model. The results from FE simulations show a longer activation length along the gap resulting in higher controllable forces values, without increasing the overall dimensions of the proposed prototype. Mon, 03 May 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=2151 https://popups.uliege.be/esaform21/index.php?id=942 Accumulative roll-bonding (ARB) is a novel plastic straining process aimed at bonding of similar and dissimilar metal combinations. Moreover, it is used recently to produce ultrafine grain materials and metal matrix reinforced composites to enhance mechanical, electrical, and corrosion resistance properties. This work presents an experimental study of roll bonding and accumulative roll bonding of similar AA3105 aluminum alloy at 300°C with a final thickness of 1.2 mm, focusing especially on bond strength evaluation and layers continuities. Tensile tests and three-points bending were performed to mechanical characterize the produced sheets in the various steps and based on the number of the cycles. The maximum strength was reached after 3 ARB cycles. After 4 cycles, the bonding interfaces have a uniform distribution through the sheet thickness, it is possible to distinguish only the interface formed in the last pass in the fracture surface, and no significant enhancement in strength was observed. Starting from 2 ARB cycles, micro-cracks were observed at the outer surface for bending angles greater than 90 deg, and at 180 deg all ARBed samples except A1 were failed. Mon, 03 May 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=942 https://popups.uliege.be/esaform21/index.php?id=4891 ESAFORM conferences would not happen without all the efforts of the Board of Directors of the association. For 24 years, without any salary, the members of the board give time and energy to launch the annual conference and new actions to fill the association objectives. We build a community and we offer networking opportunities. Friendship emerges between all these scientists who gather years after years. I thank my colleagues for the opportunity of being chairwoman of ESAFORM 2021. I organized ESAFORM in 2001 and it is a real pleasure to organize it again, in 2021. Let us be flexible even if I would have prefered to see you not on a screen and to share the progresses of Liege city in 20 years. Did you had a look at the touristic Liege visit? I thank Céline Dizier of AIM who worked hard to find solutions to organize this conference and to follow my suggestions to give not only a scientific content but also to provide some social links within this pandemic time. I had mixed feelings about giving ESAFORM money to a commercial editor as during those 23 years of proceedings, ESAFORM board could not succeed to build a long term partnership for them. Edition world is changing, authors are not happy to pay to read in classical journals and to pay again to publish in Open Access approach in the same journals or other ones sometimes far from being “fair”. Each year, the conference organizers have to fight with template problems; ghost characters to provide to the chosen editor “clea Wed, 21 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=4891 https://popups.uliege.be/esaform21/index.php?id=2599 In this study, a data-driven deep learning model for fast and accurate prediction of temperature evolution and melting pool size of metallic additive manufacturing processes are developed. The study focuses on bulk experiments of the M4 high-speed steel material powder manufactured by Direct Energy Deposition. Under non-optimized process parameters, many deposited layers (above 30) generate large changes of microstructure through the sample depth caused by the high sensitivity of the cladding material on the thermal history. A 2D finite element analysis (FEA) of the bulk sample, validated in a previous study by experimental measurements, is able to achieve numerical data defining the temperature field evolution under different process settings. A Feed-forward neural networks (FFNN) approach is trained to reproduce the temperature fields generated from FEA. Hence, the trained FFNN is used to predict the history of the temperature fields for new process parameter sets not included in the initial dataset. Besides the input energy, nodal coordinates, and time, five additional features relating layer number, laser location, and distance from the laser to sampling point are considered to enhance prediction accuracy. The results indicate that the temperature evolution is predicted well by the FFNN with an accuracy of 99% within 12 seconds. Wed, 21 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=2599 https://popups.uliege.be/esaform21/index.php?id=524 In the field of impact response of thermoplastic reinforced composites, several investigations about material behaviour in terms of delamination, indentation and fracture mechanism were conducted. Although a significant influence of the polymer temperature on the overall material impact response is expected, a limited number of studies are available in this regard. Most of the available scientific evidence concerns thermosetting composites and thermoplastic composites response only at room temperature. In particular, the purpose of this contribution is to better understand the dissipation mechanisms involved in thermoplastic reinforced composite under impact conditions for different temperatures. Starting from the few available literature data about the modelling of the problem, the aim of the present work is the development of a numerical approach able to reproduce the experimentally tested conditions. An experimental campaign on hot pressed polyamide 6 /basalt plain fabric laminates impact was selected as the benchmark for the numerical approach. The laminates impact response at increasing values of impact energy between 5J and 30J were simulated under three temperature conditions set around the polymer transition temperature (40°C, 80°C and 100°C). By validating the overall numerical model response on the room temperature experiment, considerations about the magnitude of viscous dissipation and its influence, for the different tested temperatures and in function of the adopted lamination technology, were made. Wed, 14 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=524 https://popups.uliege.be/esaform21/index.php?id=4783 EXACT Experiment and Analysis of Aluminum Cup Drawing Test The ESFORM Benchmark promotes the constitution of a network to deeply analyze a challenge present in the community of material forming processes. The earing predictions formed during the cup drawing process is an old problem (Fig.1). However here, for the first time, the organizers (see Table 1), eight well-known scientists of the ESAFORM community decide to investigate together with all the benchmark participants (Table 2) their practice in both experimental and numerical fields. The discussions and results of this work will be presented at the ESAFORM 2021 conference and gathered later within an article in the International Journal of Material Forming. The participants and the organizers together will point the impact of different choices on the results. Fig.1 Technical challenge: earing prediction for an anisotropic material Most sheet forming benchmarks include information such as: the hardening law parameters, based on limited experimental data (generally, r-values, yield stresses and ultimate strengths for 3 loading directions) extracted from uniaxial tension tests the coefficients for certain yield functions, available in the material libraries of most commercial software. The features of the ESAFORM 2021 Benchmark are : identification of constitutive models performed by participants; information concerning the experimental scatter, the “raw” data, where 3 laboratories have collaborated to duplicate some ty Tue, 13 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=4783 https://popups.uliege.be/esaform21/index.php?id=2050 We have seen in Part I of this paper that model order reduction allows the involvement of physics-based models in design, as in the past, but now also in online decision-making, without requiring unreasonable computing resources. On the other hand, machine learning techniques were not ready to cope with the processing speed and the lack of data. It was therefore necessary to adapt a number of techniques, and to create others, capable of operating online and even in the presence of a very small amount of data: the so-called "physics-informed artificial intelligence" techniques. For that purpose, we have adapted and proposed a number of techniques, which have proven and are proving every day in many industrial applications their capabilities and performances. Six major uses of AI in engineering concern: (i) visualization of multidimensional data; (ii) classification and clustering, supervised and unsupervised, where it is assumed that members of the same cluster have similar behaviors; (iii) model extraction, that is, discovering the quantitative relationship between inputs (actions) and outputs (reactions) in a consistent manner with respect to the physical laws. When addressing knowledge extraction, item (iv) above, as well as the need of explaining for certifying, item (v), advances are much limited and both items need for major progresses, as the one enabling discarding useless parameters, or discovering latent variables whose consideration becomes compulsory for explaining experimental findings, or combining parameters that act in a combined manner. Discovering equations is a very timely topic because it finally enables transforming data into knowledge. Mon, 12 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=2050 https://popups.uliege.be/esaform21/index.php?id=2056 During forming of complex fiber-metal laminates (FML), compressive stress zones occur. In pure textile forming, these compressive stresses typically lead to extensive wrinkling. In FML forming, however, wrinkling is partly hindered by the metal layers. Thus, combined stress states occur, where compression influences the deformation. In forming simulation, these compressive stresses can lead to erroneous formation of shear bands within the fabric layer, if the deformation behavior is not modelled correctly. Simple fabric models neither consider interactions between roving directions nor model interactions between membrane strains and shear strains. More advanced invariant-based hyperelastic material models are able to capture these interactions, but only consider tension and shear, while disregarding compression. A common assumption is to set the fabric compression stiffness close to zero. Experimentally, the in-plane fabric compression stiffness has not been determined so far. However, in FML forming, the compression stiffness and the combined compression-tension-shear behavior becomes relevant. In this article, the authors summarize and analyze the capacity of state-of-the-art fabric material models to predict the deformation behavior of fabrics under combined loading. Based on these findings, conclusions are drawn for a new macroscopic modeling approach for woven fabrics, including coupling of tension, compression and shear. Mon, 12 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=2056 https://popups.uliege.be/esaform21/index.php?id=2067 Mitigation of cure-induced defects in thermoset composite parts has always been a challenging problem for manufacturers especially when it comes to high dimensional accuracy of components. Thus, it is crucial to understand the evolution of the thermo-chemical properties of these materials during the totality of the curing cycle. In this paper, a new methodology is presented to characterize the process-induced strains throughout the cure. The investigation is based on the development of an existing laboratory bench named as PvT-HADDOC. The tests were performed on an interlayer toughened aerospace carbon/epoxy prepreg. Unidirectional laminate samples (105x105 mm2) of almost 6 mm of thickness were manufactured by hand lay-up then debulked at room temperature under full vacuum. The PvT-HADDOC device allows a manufacturing process following the recommended cure cycle of epoxy composites under 7 bars pressure and a temperature up to 180°C. It enables the measurements of the process-induced strains, simultaneously, along two directions: through-thickness and in-plane. Results show a complex behavior of an assumed unidirectional composite. It exhibits a temperature and time dependent compaction behavior through the thickness only. The measured thermal expansion coefficients are proved to be higher in the thickness direction for the uncured as well as for the cured state of the material. Most of the chemical shrinkage occurs along the thickness direction. This unexpected complexity is mainly attributed to the presence of interleaf layers of resin in the laminate structure. Thus, the investigated M21/IMA material is considered fully orthotropic. Mon, 12 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=2067 https://popups.uliege.be/esaform21/index.php?id=2075 Like in many other production technologies, a broad process window for metal forming is desired. The goal is always a stable process chain. One of the key aspects for metal forming are stable tribological conditions. Instabilities can be caused by, amongst others, different material batches, change in temperature during the production process, different lubricant amounts and different stroke rates. At the beginning of a production run, the tribological stability suffers from transient temperature effects caused by plastic and frictional work and a viscosity drop of the lubricant. To control the tribology, different strategies are suitable: changing the oil type, the oil amount, the blank holder force or the stroke rate. Within the EU-project ASPECT, control strategies on blank holder forces are developed as well as lubricants with improved stability on their behaviour as a function of temperature. This paper will focus on the latter. In preliminary ball on plate test the friction and wear of lubricant formulations were investigated and compared to a Reference lubricant. Followed by strip drawing and forming tests. Finally, the concept is proven in trials on a demonstrator line, which is close to serial production. Mon, 12 Apr 2021 00:00:00 +0200 https://popups.uliege.be/esaform21/index.php?id=2075