Proceedings of the 11th IEA International Workshop on Beryllium Technology (BeWS-11), Barcelona, Spain, 12-13 September 2013 (KIT Scientific Reports ; 7686)

The 11th IEA Beryllium Workshop (BeWS-11) was jointly organized by the KIT, Germany and Ciemat, Spain and was held at the Technical University of Catalonia, Barcelona Tech (UCP). The International Organizing Committee (IOC) and all participants expressed their appreciation to the Local Organizing Committee for the truly excellent organization of the workshop at Ciemat. About forty scientists participated, coming mainly from Europe, U.S.A., Russia, Japan, and Kazakhstan

Proceedings of the 10th IEA International Workshop on Beryllium Technology, September 19 - 21, 2012, Karlsruhe, Germany (KIT Scientific Reports ; 7650)

The 10th IEA Beryllium Workshop (BeWS-10) was organized by the Karlsruhe Institute of Technology (KIT) with participants from Europe, U.S.A., Russia, Japan, and Kazakhstan. The main topics of the 30 papers in the proceedings are: the overview of the Be-related activities in Europe, U.S.A., RF, and Japan, results on the Be irradiation program HIDOBE-01, beryllide intermetallic compounds, technology and safety issues, and modeling of the Be radiation resistance

Directed energy deposition-arc (DED-Arc) and numerical welding simulation as a method to determine the homogeneity

This research presents a hybrid approach to for the prediction of the homogeneity of mechanical properties in 3D metal parts manufactured using directed energy deposition-arc (DED-Arc). DED-Arc is an additive manufacturing process which can offer a cost-effective way to manufacture 3D metal parts, due to high deposition rate of up to 8 kg/h. Regression equations developed in a previous study were used to predict the mechanical properties of a wall structure using only the cooling time t8/5 calculated in a numerical welding simulation. The new approach in this research paper contains the prediction of the homogeneity of the mechanical properties, especially hardness, in 3D metal parts, which can vary due to localized changes in t8/5 cooling time provoked by specific geometrical features or general changes in dimensions. In this study a method for the calculation of the hardness distribution on additively manufactured parts was developed and shown

Detecting Process Anomalies in the GMAW Process by Acoustic Sensing with a Convolutional Neural Network (CNN) for Classification

Today, the quality of welded seams is often examined off-line with either destructive or non-destructive testing. These test procedures are time-consuming and therefore costly. This is especially true if the welds are not welded accurately due to process anomalies. In manual welding, experienced welders are able to detect process anomalies by listening to the sound of the welding process. In this paper, an approach to transfer the “hearing” of an experienced welder into an automated testing process is presented. An acoustic measuring device for recording audible sound is installed for this purpose on a fully automated welding fixture. The processing of the sound information by means of machine learning methods enables in-line process control. Existing research results until now show that the arc is the main sound source. However, both the outflow of the shielding gas and the wire feed emit sound information. Other investigations describe welding irregularities by evaluating and assessing existing sound recordings. Descriptive analysis was performed to find a connection between certain sound patterns and welding irregularities. Recent contributions have used machine learning to identify the degree of welding penetration. The basic assumption of the presented investigations is that process anomalies are the cause of welding irregularities. The focus was on detecting deviating shielding gas flow rates based on audio recordings, processed by a convolutional neural network (CNN). After adjusting the hyperparameters of the CNN it was capable of distinguishing between different flow rates of shielding gas

Production of Topology-optimised Structural Nodes Using Arc-based, Additive Manufacturing with GMAW Welding Process

The desire to generate a stress optimised structural node with maximum stability is often coupled with the goal of low manufacturing costs and an adapted and minimal use of material. The complex, three-dimensional free-form structures, which are created by means of topology-optimisation, are only partially suitable for conventional manufacturing. The wire arc additive manufacturing (WAAM), by means of arc welding processes, offer a cost-effective and flexible possibility for the individual production of complex, metallic components. Gas metal arc welding (GMAW) is particularly suitable to produce large-volume, load-bearing structures due to build-up rates of up to 5 kg/h. The generation of strength and stiffness adapted support structures by means of the numerical simulation method of topology-optimisation was investigated in this study to generate topology-optimised structural nodes. The resulting node is transferred into a robot path using CAD/CAM software and manufactured from the filler material G4Si1 using WAAM with the GMAW process. Based on the boundary conditions of the WAAM process, the path planning and thus the manufacturability of the topology-optimised supporting structure nodes is evaluated and verified using a sample structure made of the welding filler material G4Si1. Depending on the path planning, an improvement of the mechanical properties could be achieved, due to changes in t8/5 times

Surmounting Oscillating Barriers

Thermally activated escape over a potential barrier in the presence of periodic driving is considered. By means of novel time-dependent path-integral methods we derive asymptotically exact weak-noise expressions for both the instantaneous and the time-averaged escape rate. The agreement with accurate numerical results is excellent over a wide range of driving strengths and driving frequencies.Comment: 4 pages, 4 figure

Pebble bed packing in square cavities (KIT Scientific Reports ; 7631)

The dense packing of granular materials (pebble beds) in cavities is important in many technical applications. Results are presented from i) analyses of tomography investigations in the European Synchrotron Radiation Facility (ESRF), Grenoble, and ii) packing experiments with different types of spherical and non-spherical particles using Plexiglas containers dominated by flat walls

Directed energy deposition-arc (DED-Arc) and numerical welding simulation as a hybrid data source for future machine learning applications

This research presents a hybrid approach to generate sample data for future machine learning applications for the prediction of mechanical properties in directed energy deposition-arc (DED-Arc) using the GMAW process. DED-Arc is an additive manufacturing process which offers a cost-effective way to generate 3D metal parts, due to its high deposition rate of up to 8 kg/h. The mechanical properties additively manufactured wall structures made of the filler material G4Si1 (ER70 S-6) are shown in dependency of the t8/5 cooling time. The numerical simulation is used to link the process parameters and geometrical features to a specific t8/5 cooling time. With an input of average welding power, welding speed and geometrical features such as wall thickness, layer height and heat source size a specific temperature field can be calculated for each iteration in the simulated welding process. This novel approach allows to generate large, artificial data sets as training data for machine learning methods by combining experimental results to generate a regression equation based on the experimentally measured t8/5 cooling time. Therefore, using the regression equations in combination with numerically calculated t8/5 cooling times an accurate prediction of the mechanical properties was possible in this research with an error of only 2.6%. Thus, a small set of experimentally generated data set allows to achieve regression equations which enable a precise prediction of mechanical properties. Moreover, the validated numerical welding simulation model was suitable to achieve an accurate calculation of the t8/5 cooling time, with an error of only 0.3%

Intestinal Colonization of IL-2 Deficient Mice with Non-Colitogenic B. vulgatus Prevents DC Maturation and T-Cell Polarization

BACKGROUND: IL-2 deficient (IL-2(-/-)) mice mono-colonized with E. coli mpk develop colitis whereas IL-2(-/-)-mice mono-colonized with B. vulgatus mpk do not and are even protected from E. coli mpk induced colitis. METHODOLOGY/PRINCIPAL FINDINGS: We investigated if mono-colonization with E. coli mpk or B. vulgatus mpk differentially modulates distribution, activation and maturation of intestinal lamina propria (LP) dendritic cells (DC). LP DC in mice mono-colonized with protective B. vulgatus mpk or co-colonized with E. coli mpk/B. vulgatus mpk featured a semi-mature LP DC phenotype (CD40(lo)CD80(lo)MHC-II(hi)) whereas mono-colonization with colitogenic E. coli mpk induced LP DC activation and maturation prior to onset of colitis. Accordingly, chemokine receptor (CCR) 7 surface expression was more strikingly enhanced in mesenteric lymph node DC from E. coli mpk than B. vulgatus mpk mono- or co-colonized mice. Mature but not semi-mature LP DC promoted Th1 polarization. As B. vulgatus mpk promotes differentiation of semi-mature DC presumably by IL-6, mRNA and protein expression of IL-6 was investigated in LP DC. The data demonstrated that IL-6 mRNA and protein was increased in LP DC of B. vulgatus mpk as compared to E. coli mpk mono-colonized IL-2(-/-)-mice. The B. vulgatus mpk mediated suppression of CCR7 expression and DC migration was abolished in IL-6(-/-)-DC in vitro. CONCLUSIONS/SIGNIFICANCE: From this data we conclude that the B. vulgatus triggered IL-6 secretion by LP DC in absence of proinflammatory cytokines such as IL-12 or TNF-alpha induces a semi-mature LP DC phenotype, which might prevent T-cell activation and thereby the induction of colitis in IL-2(-/-)-mice. The data provide new evidence that IL-6 might act as an immune regulatory cytokine in the mucosa by targeting intestinal DC

Molecular Wires Acting as Coherent Quantum Ratchets

The effect of laser fields on the electron transport through a molecular wire being weakly coupled to two leads is investigated. The molecular wire acts as a coherent quantum ratchet if the molecule is composed of periodically arranged, asymmetric chemical groups. This setup presents a quantum rectifier with a finite dc-response in the absence of a static bias. The nonlinear current is evaluated in closed form within the Floquet basis of the isolated, driven wire. The current response reveals multiple current reversals together with a nonlinear dependence (reflecting avoided quasi-energy crossings) on both, the amplitude and the frequency of the laser field. The current saturates for long wires at a nonzero value, while it may change sign upon decreasing its length.Comment: 4 pages, 4 figures, RevTeX