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- 8.1 Sensorik, mess- und prüftechnische Verfahren (42) (entfernen)
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The mechanical and geometrical properties of impact targets greatly influence the outcome of a drop test. The International Agreement concerning the International Carriage of Dangerous Goods by Road (ADR) as well as ISO 2248 describe the characteristics of impact targets for drop tests of dangerous goods packagings.
According to these regulations, the impact target’s surface needs to be unyielding, under testing conditions non-deformable, flat, and integral with a mass at least 50 times that of the heaviest packaging to be tested. The problem is that many production facilities, especially manufacturers of corrugated fibreboard boxes, do not have their own testing device with the required 50 times mass ratio of the impact target for a regulation compliant drop test during series production. Furthermore, at UN level it is considered necessary to revise these requirements.
In the present paper, the impact target requirements are examined in detail and compared with those in other technical areas (e.g., impact target for container for the transport of radioactive materials). A research method is being developed to investigate the dependency between the mass ratio of the packaging and the target as well as the damage resistance of a drop tested package in relation to specific design characteristics. The results are of high relevance for industry purposes and intended to ensure a uniform level of safety assessment for the mechanical testing of dangerous goods packagings.
Till now application of printed magnetoelectronics is hindered by lack of large area exchange coupled metallic multilayers required to produce printable magneto-sensory inks. Large-scale roll-to-roll (R2R) fabrication process is an attractive approach owing to its capabilities for high volume, high throughput, and large area manufacturing. Precise and high performance R2R sputtering technology is developed to fabricate large area giant magnetoresistive (GMR) thin-films stacks that contain 30 metallic bilayers prepared by continuous R2R sputtering of Co and Cu sequential on a hundred meters long polyethylene terephthalate (PET) web. The R2R sputtered Co/Cu multilayer on a 0.2 × 100 m2 PET web exhibits a GMR ratio of ≈40% achieving the largest area exchange coupled room temperature magneto-sensitive system demonstrated to date. The prepared GMR thin-film is converted to magnetosensitive ink that enables printing of magnetic sensors with high performance in a cost-efficient way, which promotes integration with printed electronics. An average GMR ratio of ≈18% is obtained for 370 printed magnetic sensors. The realized precise R2R sputtering approach can also be extended to a wide range of hybrid thin-film material systems opening up a path for new functional inks applied with printing technologies.
Nach einer kurzen Einführung in die Schallemissionsprüfung und -Analyse wird ein Versuchsstand vorgestellt, der im Rahmen des Themenfeldprojektes Seal Waste Safe installiert wurde. Schwerpunkt des Vortrages sind die Schallemissionsmessungen an einem 150 l Demonstrator aus Salzbeton und einem weiteren aus alkali-aktiviertem Material. Neben der konventionellen Schallemissionsanaylse mit Aktivitäts- und Intensitätsparametern der Zeitsignale, werden auch frequenzbasierte Parameter zur Analyse andiskutiert.
Gas distribution mapping is important to have an accurate understanding of gas concentration levels in hazardous environments. A major problem is that in-situ gas sensors are only able to measure concentrations at their specific location. The gas distribution in-between the sampling locations must therefore be modeled. In this research, we interpret the task of spatial interpolation between sparsely distributed sensors as a task of enhancing an image's resolution, namely super-resolution. Because autoencoders are proven to perform well for this super-resolution task, we trained a convolutional encoder-decoder neural network to map the gas distribution over a spatially sparse sensor network. Due to the difficulty to collect real-world gas distribution data and missing ground truth, we used synthetic data generated with a gas distribution simulator for training and evaluation of the model. Our results show that the neural network was able to learn the behavior of gas plumes and outperforms simpler interpolation techniques.
Gas distribution mapping is important to have an accurate understanding of gas concentration levels in hazardous environments. A major problem is that in-situ gas sensors are only able to measure concentrations at their specific location. The gas distribution in-between the sampling locations must therefore be modeled. In this research, we interpret the task of spatial interpolation between sparsely distributed sensors as a task of enhancing an image's resolution, namely super-resolution. Because autoencoders are proven to perform well for this super-resolution task, we trained a convolutional encoder-decoder neural network to map the gas distribution over a spatially sparse sensor network. Due to the difficulty to collect real-world gas distribution data and missing ground truth, we used synthetic data generated with a gas distribution simulator for training and evaluation of the model. Our results show that the neural network was able to learn the behavior of gas plumes and outperforms simpler interpolation techniques.
The mechanical and geometrical properties of impact targets greatly influence the outcome of a drop test. The International Agreement concerning the International Carriage of Dangerous Goods by Road (ADR) as well as ISO 2248 describe the characteristics of impact targets for drop tests of dangerous goods packagings.
According to these regulations, the impact target’s surface needs to be unyielding, under testing conditions non-deformable, flat, and integral with a mass at least 50 times that of the heaviest packaging to be tested. The problem is that many production facilities, especially manufacturers of corrugated fibreboard boxes, do not have their own testing device with the required 50 times mass ratio of the impact target for a regulation compliant drop test during series production. Furthermore, at UN level it is considered necessary to revise these requirements.
In the present paper, the impact target requirements are examined in detail and compared with those in other technical areas (e.g., impact target for container for the transport of radioactive materials). A research method is being developed to investigate the dependency between the mass ratio of the packaging and the target as well as the damage resistance of a drop tested package in relation to specific design characteristics. The results are of high relevance for industry purposes and intended to ensure a uniform level of safety assessment for the mechanical testing of dangerous goods packagings.
The finite volume method (FVM), like the finite element method (FEM), is a numerical method for determining an approximate solution for partial differential equations. The derivation of the two methods is based on very different considerations, as they have historically evolved from two distinct engineering disciplines, namely solid mechanics and fluid mechanics. This makes FVM difficult to learn for someone familiar with FEM. In this paper we want to show that a slight modification of the FEM procedure leads to an alternative derivation of the FVM. Both numerical methods are starting from the same strong formulation of the problem represented by differential equations, which are only satisfied by their exact solution. For an approximation of the exact solution, the strong formulation must be converted to a so-called weak form. From here on, the two numerical methods differ. By appropriate choice of the trial function and the test function, we can obtain different numerical methods for solving the weak formulation of the problem. While typically in FEM the basis functions of the trial function and test function are identical, in FVM they are chosen differently. In this paper, we show which trial and test function must be chosen to derive the FVM alternatively: The trial function of the FVM is a “shifted” trial function of the FEM, where the nodal points are now located in the middle of an integration interval rather than at the ends. Moreover, the basis functions of the test function are no longer the same as those of the trial function as in the FEM, but are shown to be a constant equal to 1. This is demonstrated by the example of a 1D Poisson equation.
In this talk, general aspects of the safety and acceptance of hydrogen technologies were presented. How can trust in new technologies be built when past accidents led to myths and fairy tales? The presentation does away with general prejudices and shows that handling hydrogen is neither more unsafe nor safer than handling other fuel gases. The basis for the safe handling of hydrogen is always a risk analysis.
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or poorly accessible areas. A challenging task however, is the generation of three-dimensional distribution maps from these spatially sparse gas measurements. To obtain high-quality reconstructions, the choice of optimal measuring poses is of great importance. Remote gas sensors, that are commonly used in Robot Assisted Gas Tomography (RAGT), require reflecting surfaces within the sensor’s range, limiting the possible sensing geometries, regardless of whether the robots are ground-based or airborne. By combining ground and aerial robots into a heterogeneous swarm whose agents are equipped with reflectors and remote gas sensors, remote inter-robot gas measurements become available, taking RAGT to the next dimension – releasing those constraints. In this paper, we demonstrate the feasibility of drone-to-drone measurements under realistic conditions and highlight the resulting opportunities.