Papers by Keyword: Material Characterization

Abstract: Metal-polymer-metal (mpm) sandwich sheets are considered a lightweight alternative to conventional steel sheets in the automotive industry. First studies have experimentally and numerically demonstrated the use of mpm-sandwiches in automotive crash structures. However, the sandwich forming process can compromise the crash performance through pre-damage. Finite element simulations could help predict the forming process and its limits. Current simulation approaches, however, consider neither strain rate effects and failure of the polymer and the adhesive, respectively, nor do they study the influence of inevitable material variabilities on the forming and failure behavior. In this work, a detailed finite element model of the core materials is developed. An approach for the determination of the stress strain rate dependency is proposed by evaluating the local strains on the surface, which allows to capture the main material behavior with little effort. Additional specialized tensile tests and lap-shear tests provide information about the failure of the polymer and the adhesive, respectively. Validation of the core materials model is achieved by comparing the cover layer displacements of swivel bending specimens in experiment and simulation. The influence of material variabilities on the forming and failure behavior is studied in a full factorial material parameter sweep of simulated lap-shear tests and the applicability of the model to the simulation of bending processes is demonstrated. The results prove the applicability of the proposed material characterization methods, while the parameter study and the bending simulations show how the model can be used to predict a sandwich’s formability and failure modes.

Abstract: In order to reliably predict a material’s behavior during the forming process, robust calculations with precisely calibrated material models are required. Especially when it comes to mapping phenomena depending on complex interactions of different effects, sophisticated measuring techniques have to be used in order to capture them sufficiently. Springback of sheet metal components is governed by elastic behavior, determined by geometry and current material properties. While well understood for most materials, dual-phase steels are exceptional due to their non-linear elasticity and pronounced kinematic hardening, which strongly affect elastic response. Kinematic hardening is characterized via the Bauschinger coefficient from tension–compression tests. As the Bauschinger effect depends on pre-strain and strain rate, precise crosshead control is essential. Therefore, state-of-the art characterization techniques control the process speed by calculating the crosshead velocity from the pre-set clamping length and strain rate. This method, however, does not account for setup-related influences such as machine stiffness or specimen slippage. Therefore, to improve the characterization accuracy of the Bauschinger effect, an alternative method for crosshead control during the tensile-compression test is introduced and analyzed in this study. To compare this innovative approach with the conventional one, both methods are used to capture the effect of relaxation on the Bauschinger effect with different dual-phase and mild steel. The mentioned novel method is based on the optical strain rate control during tensile tests by Naumann, using Digital Image Correlation with an Aramis setup by ZEISS. The intended pre-strain before load reversal is actively controlled by measuring the strain in situ. After characterizing the material cards for each setup, the resulting Chaboche-Rousselier curves are compared to the experimental ones. The results demonstrate that the applied method provides a reliable proof of concept and achieves precision comparable to, as well as exceeding, the conventional displacement strain rate control method.

Abstract: In the global transition towards renewable energy, a leading role is played by photovoltaic (PV) technologies. However, the increasing growth of installed PV panels, together with the rise of the number of modules reaching their end-of-life phase, make the sustainable management of electronic waste a crucial aspect. The reduction of energy consumption and polluting emissions and the maximization of material recovery represent the ultimate purpose of demanufacturing processes. Here, cryogenic delamination is proposed as an innovative strategy, as it exploits the thermal and mechanical properties of PV module constituents to achieve the cleanest possible separation of layers, allowing for the recovery of strategic materials (silicon, aluminium, silver, copper). This work aims to combine experimental and numerical approaches in order to obtain a comprehensive understanding of the fundamental mechanisms governing the process: the overall objective is represented by the process optimization to enable the exploration of various operating conditions without the need for costly and time-intensive experimental campaigns and, ultimately, the implementation of such technology at the industrial scale.

Abstract: During the hot bulk forming of long parts, inhomogeneous distributions of deformations and temperatures occur. The gradients of these distributions lead to complex, overlaying residual stresses, which can cause critical geometric deviations and mechanical failures. Common finite element (FE)-simulations for designing a process are in principle capable to predict the thermal, mechanical and metallurgical effects, but require extended material models. Thereby, the total strain increment can be described through the partial strain components of the elastic, plastic, thermal transformation related and transformation plasticity strain. To allow the numerical prediction of the distortion of long hot formed parts, an experimental characterisation of the TRIP and backflow effects is presented for the steel 31CrMoV9. Time temperature transformation (TTT) and continuous cooling transformation (CCT) diagrams are determined with JMatPro and verified by means ofmicrostructure analysis and hardness measurements. Based on these diagrams, the transformation plasticity is investigated through dilatometric tests whereby tensile and compressive loads are applied during the phase transformation. The martensite phase transformation showed the highest amounts of TRIP strains, whilst the bainite transformation exhibited lower strains but a high tensile backflow strain. For perlite the beginning of the phase transformation was delayed and its duration extended due to the induced loads.

Abstract: This paper revisits the long-standing question of how to fully characterise the in-plane plastic anisotropy of sheet metals without assembling evidence from multiple standardised tests. The central idea is pragmatic: a single, well-designed heterogeneous biaxial experiment can replace the conventional combination of uniaxial and equibiaxial tests if the specimen and the inverse identification method are co-designed to (i) activate informative stress states and (ii) maintain low strain gradients for accurate digital image correlation measurements. The proposed cruciform specimen is deliberately conceived as a benchmark configuration for full-field inverse identification, with known locations and stress-strain states at which relevant material information is embedded. The approach is coupled with a Finite Element Model Updating framework, enabling all anisotropy parameters of the YLD2000-2d model to be identified from a single full-field dataset. Sensitivity and identifiability analyses demonstrate that a physically based parameter formulation significantly improves the conditioning of the inverse problem. Virtual experimentation confirms the robustness and accuracy of the proposed “one-test” identification strategy.

Abstract: Material Testing 2.0 (MT2.0) couples full‑field deformation measurements (Digital Image Correlation, DIC) with inverse identification methods (Virtual Fields Method, VFM) to extract constitutive parameters from a small number of heterogeneous experiments. This paper presents the Cut‑Clamp‑Play concept: an integrated industrial MT2.0 solution that unifies specimen design, automated testing hardware, and a computationally efficient VFM identification chain to deliver fast, user‑friendly sheet‑metal characterization. A perforated cruciform specimen is optimized for parameter identifiability of the Yld2000‑2d anisotropic yield function and used in a single biaxial test. A working prototype has been built at KU Leuven and used to collect representative DIC data; the measured displacement/strain response is double‑symmetric, confirming correct mechanical operation. Projected and early prototype results indicate that the Cut‑Clamp‑Play approach can reduce operator actions by roughly 70% and produce identification results within one hour for typical sheet‑metal cases, while further work is required to make the fully automated “Play” stage robust for industrial deployment.

Abstract: Materials characterization and the knowledge of their elastic-plastic behavior are of fundamental importance for the design of industrial manufacturing processes. Nowadays, FEM simulation is the main tool used to optimize product quality and minimize scraps, and the numerical codes have evolved over the years to obtain accurate solutions with reduced computational times. Nevertheless, in order to perform reliable simulations, it is necessary to include accurate modeling of the material flow stress. Hot torsion is a powerful method for the characterization of the material flow stress because, tests can be carried out at constant speeds and temperatures, reaching large strain values, and thus getting over the limits of compression and tensile tests. In this paper the hot torsion characterization applied to AA6082 alloy is presented: tests were performed with equivalent strain rates of 0.01, 0.1, 1, and 10 s^-1, in the temperature range from 440 to 550 °C (from 713.15 to 823.15 K). The results are presented in terms of equivalent stress vs equivalent strain. Finally, the material flow stress curve was predicted by the Hyperbolic sine model and Hensel-Spittel law, and the material parameters A, m_1-9 are provided for the temperature expressed in °C and K.

Abstract: Materials are a core part of the development in mechanical turbines, where there is always potential for life-improvement. The demand for alloys with durability, low cost, and long service cycles are evergreen. The materials used in turbomachinery must have excellent resistance to thermal fatigue, as well as high temperature oxidation and corrosion resistance. Good creep resistance is also an important consideration, especially for large blades and multi-airfoil latter stage nozzles. Development of new alloy compositions and material characterization plays a critical role in advanced machinery evolution. In this work, some of the available characterization methods are applied to analyze and study the effect of heat treatment, service effect and aging on alloys.

Abstract: Increased waste as a result of unsustainable industrialization, urbanization, and agriculturalization is a serious threat to the comfort of human life. Our ecosystem has been severely damaged by the production and disposal of massive amounts of harmful materials and pollutants. Technologies must be created to eliminate or drastically reduce hazardous waste and pollutants from the environment. By using agricultural waste and by-products to create environmentally acceptable adsorbents, adsorption is one way for removing pollutants from water and waste water. It is crucial to evaluate the capability of various produced adsorbents and determine how well they can be used to treat water and wastewater. To address this, research is being done on characterizing these materials. Proximate analysis, thermal gravimetric analysis, FTIR, SEM, energy dispersive X-ray analysis (EDS), BET surface area analysis, and X-ray diffraction are used to analyze agricultural wastes. According to XRD studies, agro-based adsorbents have an amorphous structure, which is a benefit for well-defined porous adsorbents. Development of good porosity occurred in all materials due to chemical treatment given to materials, which was evident from SEM images and results of BET analysis. Adsorbents prepared from agricultural wastes had large surface area ranging from 950-1200 m²/g, which makes them efficient adsorbents like conventionally used charcoal. EDS test results also shows that normal carbon content is in range 57 to 59% which is good for adsorption. Proximate analysis and bulk density also supported that developed adsorbents has the great potential. Agro-based adsorbents are efficient adsorbent which is a good alternative to conventionally and commercially available activated charcoal.

Abstract: The ongoing digitization of production processes provides new possibilities and potentials for process monitoring of forming and stamping processes. The component quality achievable by these processes is strongly dependent on the properties of the sheet metal material, so that a permanent digital recording of material data offers high potential for monitoring each component produced. In this context, presented paper deals with a novel AI-based method for the direct determination of ma-terial parameters from measured punching force curves. Using software systems Python and Tensor-Flow, an artificial neural network was first set up to determine mechanical material parameters (out-put data) from punching force curves (input data). As data basis for the adopted neural network, force curves were measured during punching of various sheet metal materials using a punching tool equipped with a direct force measurement device. Punching force curves were experimentally deter-mined for the sheet metal materials DP1200, DP1000, DP800, DP600, HX380LA, DC03 and DX54. Additionally, tensile tests were performed for these sheet metal materials to determine ultimate tensile strengths (Rm), yield strengths (Rp0.2, Re), uniform strains (Ag), elongations at break (At) and strain hardening exponents (n). The presented paper reveals that neural networks can accurately quantify the relationship between characteristic parameters of punching force curves and the mentioned me-chanical material properties.