Beanspruchungsgerechtes Konstruieren : Kopplung von CAD und FEM

Die Kopplung der Bereiche CAD und FEM ist ein wesentlicher Schritt hin zu dem übergeordneten Ziel des fertigungsgerechten und beanspruchungsgerechten Konstruierens. Neue Bauteile werden mit CAD-Systemen entworfen und deren mechanische Eigenschaften anschließend mittels FEM-Systemen analysiert. Da diese Systeme auf ähnlichen Bauteilgeometrien aufbauen, ist es naheliegend, die im CAD-System vorliegende Geometriebeschreibung für die FEM-Analyse zu übernehmen. Ein direkter Austausch der Geometriedaten scheitert jedoch, da sich die jeweiligen Geometriemodelle stark unterscheiden. Aus diesem Grunde findet herkömmlicherweise kein rechnergestützter Datenaustausch statt. In dieser Arbeit berichten wir über die Konzepte, die Realisierung sowie über erste praktische Einsatzerfahrungen und Systembewertung zu einem Geometrie-Transformator (entwickelt für die Systeme EUCLID und ANSYS), der eine (weitestgehend) automatische Umsetzung der Geometriedarstellungen durchführt und somit einen durchgängigen rechnerunterstützten Prozeß für die Konversion vom CAD- zum FEM-Modell ermöglicht.The coupling of the two areas of computeraided design (CAD) and finite-element analyses (FEM) marks an important step towards the overall goal of manufacturing and stress-optimized design. New parts are developed with the help of CAD systems and their mechanical and stress characteristics are analysed by means of FEM systems. Since both system types rely on similar geometry it is straightforward to use the CAD geometry also for FEM purposes. A direct exchange of the geometry data will fail because the two geometries are quite different. In this article we report on the concepts, the realization as well as on first practical experiences and system assessment to a so-called geometry-transformer (designed for the EUCLID system and the ANSYS system), which employs an automatic geometry transformation, thus realizing a computer-supported conversion from CAD to FEM geometry

Prevent Low-Quality Analytics by Automatic Selection of the Best-Fitting Training Data

Data analysis pipelines consist of a sequence of various analysis tools. Most of these tools are based on supervised machine learning techniques and thus rely on labeled training data. Selecting appropriate training data has a crucial impact on analytics quality. Yet, most of the times, domain experts who construct analysis pipelines neglect the task of selecting appropriate training data. They rely on default training data sets, e.g., since they do not know which other training data sets exist and what they are used for. Yet, default training data sets may be very different from the domain-specific input data that is to be analyzed, leading to low-quality results. Moreover, these input data sets are usually unlabeled. Thus, information on analytics quality is not measurable with evaluation metrics. Our contribution comprises a method that (1) indicates the expected quality to the domain expert while constructing the analysis pipeline, without need for labels and (2) automatically selects the best-fitting training data. It is based on a measurement of the similarity between input and training data. In our evaluation, we consider the part-of-speech tagger tool and show that Latent Semantic Analysis (LSA) and Cosine Similarity are suited as indicators for the quality of analysis results and as basis for an automatic selection of the best-fitting training data

Efficient and Flexible Technology for Binder Roving Manufacturing

Liquid Composite Molding (LCM) processes are state of the art for the manufacturing of Fiber Reinforced Polymer Composites (FRPC). In the present paper a newly developed method for the manufacturing of binder rovings is defined. The binder roving consists of heavy tow carbon fibers combined with thermoset binder material. Different manufacturing units, such as the binder conveying system or the binder application system, were developed and optimized regarding the distribution quality and the output rate. For all tests a 50k SGL roving and a Huntsman XB 3366 binder material were used as input material

Influence of Textile Reinforcement on Bending Properties and Impact Strength of SMC-components

In Europe, Sheet Molding Compound (SMC) has high market relevance in the field of glass fiber reinforced polymer composites with a market share of almost 20% in terms of mass. The material has a thermal expansion coefficient similar to steel and special grades show Class-A surface quality being thereby an appreciated material in the automotive industry. The mechanical properties of SMC components and thus its implementation in new application fields are mainly limited by the type of fiber and fiber length. The project “Preform-SMC” analyzed the combination of the standard SMC process (chopped long fibers) and the preform technology (textiles) in order to improve the overall performance of components. The studies revealed that the quality of the impregnation of the preform material is mainly determined by the density and thus the filler content of the SMC semi-finished product and the layer structure of the reinforcing fibers. Locally implemented reinforcing textiles improve, by implementing endless fibers among load paths, the mechanical properties. Depending on the fiber type and the layer structure e.g. impact strength and absorbed energy could at least be doubled

Volumetric Interaction and Material Characterization of Flax/Furan Bio-composites

This paper deals with the characterization of a green composite, made of flax fibers and a bio-derived furan resin. It is shown that the porosity within the composite, which is determined by various parameters, adversely influences the mechanical performance as well as the water absorption behavior of the material. Since the furan resin induces a large amount of porosity during curing due to its foaming characteristic, the aim of this study is to find a method in order to minimize this so-called structural porosity. Therefore it is paid special attention to the conversion between weight and volume fractions and the volumetric interaction of the constituent phases. A model is applied in order to predict and minimize the porosity content in the composite

Towards Probing Conformational States of Y2 Receptor Using Hyperpolarized 129Xe NMR

G protein-coupled receptors can adopt many different conformational states, each of them exhibiting different restraints towards downstream signaling pathways. One promising strategy to identify and quantify this conformational landscape is to introduce a cysteine at a receptor site sensitive to different states and label this cysteine with a probe for detection. Here, the application of NMR of hyperpolarized 129Xe for the detection of the conformational states of human neuropeptide Y2 receptor is introduced. The xenon trapping cage molecule cryptophane-A attached to a cysteine in extracellular loop 2 of the receptor facilitates chemical exchange saturation transfer experiments without and in the presence of native ligand neuropeptide Y. High-quality spectra indicative of structural states of the receptor–cage conjugate were obtained. Specifically, five signals could be assigned to the conjugate in the apo form. After the addition of NPY, one additional signal and subtle modifications in the persisting signals could be detected. The correlation of the spectroscopic signals and structural states was achieved with molecular dynamics simulations, suggesting frequent contact between the xenon trapping cage and the receptor surface but a preferred interaction with the bound ligand

Influence of Fabric Parameters on Surface Waviness of FRPC: An Experimental Investigation and Development of a Model on Surface Waviness

This paper deals with the surface development of continuous fiber-reinforced thermoplastic composites, so called organic sheets, during processing. To investigate the effect of the textile parameters on the surface development organic sheets with different steel wire fabrics and a polycarbonate matrix were manufactured using a laboratory press. The fabrics differed in fiber diameter and mesh size. The results showed that both textile parameters have a significant influence on the characteristic surface waviness of the FRPC. Increasing fiber diameters and mesh sizes lead to higher maximum waviness. Organic sheets with a fiber diameter of the reinforcement less or equal 50 μm could not be differentiated anymore and had no visible waviness. Based on the equation for linear thermal expansion a thermo rheological process model was developed to predict the surface waviness. The model describes the waviness creation including a pressure induced compensating polymer flow. A waviness comparison of experimental data with calculated results shows a good agreement

SQL/XNF - processing composite objects as abstractions over relational data

An extension to SQL, called the SQL extended normal form (XNF), is discussed. It enhances relational technology by a composite object facility, which comprises not only extraction of composite objects from existing databases but also efficient navigation and manipulation facilities provided by an appropriate application programming interface. The language itself allows sharing of the database among normal form SQL applications and composite object applications. It provides proper subsetting of the database and subsequent structuring, exploiting subobject sharing and recursion, all based on its powerful composite object constructor concept, which is closed under the language operations. XNF is integrated into the relational framework, thus benefiting from the available technology such as relational engine and query optimization

Advanced Measurement, Characterization and Simulation of Thermoplastic Composite Induction Welding

Induction welding is a highly versatile thermoplastic composite (TPC) and hybrid material (metal to composite) fusion bonding process which uses electromagnetic phenomena to generate contact-free heating of the joining partners. Two highly influential sets of parameters in the process are the ‘actual’ applied coil current amplitude and frequency along with the temperature and frequency dependent electrical conductivity behavior of the joining materials. Both sets of data are not easily measurable and may change dynamically during the process. One of these issues can be addressed from an electrical engineering point of view, which focusses on the induction heating equipment itself and accurate measurement of the electrical behavior of the induction heating circuit. Magnetoresistive sensors especially designed for high-frequency current measurement can be used to measure the coil current and its corresponding waveform for any welding setup. The data recorded by the sensor board, together with Fourier Transform analysis techniques, provides accurate values for the coil current and frequency, which can then be used for process and equipment design simulations assisting in the development of suitable control systems and overall process optimization

The Chandra Source Catalog

The Chandra Source Catalog (CSC) is a general purpose virtual X-ray astrophysics facility that provides access to a carefully selected set of generally useful quantities for individual X-ray sources, and is designed to satisfy the needs of a broad-based group of scientists, including those who may be less familiar with astronomical data analysis in the X-ray regime. The first release of the CSC includes information about 94,676 distinct X-ray sources detected in a subset of public ACIS imaging observations from roughly the first eight years of the Chandra mission. This release of the catalog includes point and compact sources with observed spatial extents <~ 30''. The catalog (1) provides access to the best estimates of the X-ray source properties for detected sources, with good scientific fidelity, and directly supports scientific analysis using the individual source data; (2) facilitates analysis of a wide range of statistical properties for classes of X-ray sources; and (3) provides efficient access to calibrated observational data and ancillary data products for individual X-ray sources, so that users can perform detailed further analysis using existing tools. The catalog includes real X-ray sources detected with flux estimates that are at least 3 times their estimated 1 sigma uncertainties in at least one energy band, while maintaining the number of spurious sources at a level of <~ 1 false source per field for a 100 ks observation. For each detected source, the CSC provides commonly tabulated quantities, including source position, extent, multi-band fluxes, hardness ratios, and variability statistics, derived from the observations in which the source is detected. In addition to these traditional catalog elements, for each X-ray source the CSC includes an extensive set of file-based data products that can be manipulated interactively.Comment: To appear in The Astrophysical Journal Supplement Series, 53 pages, 27 figure