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Eingeladener Vortrag
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In failure analysis, micro-fractographic analysis of fracture surfaces is usually performed based on practical knowledge which is gained from available studies, own comparative tests, from the literature, as well as online databases. Based on comparisons with already existing images, fracture mechanisms are determined qualitatively. These images are mostly two-dimensional and obtained by light optical and scanning electron imaging techniques. So far, quantitative assessments have been limited to macrocopically determined percentages of fracture types or to the manual measurement of fatigue striations, for example. Recently, more and more approaches relying on computer algorithms have been taken, with algorithms capable of finding and classifying differently structured fracture characteristics. For the Industrial Collective Research (Industrielle Gemeinschaftsforschung, IGF) project “iFrakto” presented in this paper, electron-optical images are obtained, from which topographic information is calculated. This topographic information is analyzed together with the conventional 2D images. Analytical algorithms and deep learning are used to analyze and evaluate fracture characteristics and are linked to information from a fractography database. The most important aim is to provide software aiding in the application of fractography for failure analysis. This paper will present some first results of the project.
Differential Scanning Calorimetry (DSC) may be used to avoid testing for explosive and self-reactive properties according to the legal regulations of chemicals substances and dangerous goods.
Demonstrated measured exothermic decomposition energy value significantly affected by numerous factors - choice of sample vessel, sample mass, baseline shape, peak shape, heating rate.
The characterization of technical lignins is a key step for the efficient use and processing of this material into valuable chemicals and for quality control. In this study 31 lignin samples were prepared from different biomass sources (hardwood, softwood, straw, grass) and different pulping processes (sulfite, Kraft, organosolv). Each lignin was analysed by attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy. Statistical analysis of the ATR-FT-IR spectra by means of principal component analysis (PCA) showed significant differences between the lignins. Hence, the samples can be separated by PCA according to the original biomass. The differences observed in the ATR-FT-IR spectra result primarily from the relative ratios of the p-hydroxyphenyl, guaiacyl and syringyl units. Only limited influence of the pulping process is reflected by the spectral data. The spectra do not differ between samples processed by Kraft or organosolv processes. Lignosulfonates are clearly distinguishable by ATR-FT-IR from the other samples. For the classification a model was created using the k-nearest neighbor (k NN) algorithm. Different data pretreatment steps were compared for k=1…20. For validation purposes, a 5-fold cross-validation was chosen and the different quality criteria Accuracy (Acc), Error Rate (Err), Sensitivity (TPR) and specificity (TNR) were introduced. The optimized model for k=4 gives values for Acc = 98.9 %, Err = 1.1 %, TPR = 99.2 % and TNR = 99.6 %.
This is a short review on ongoing work and interests in Division 2.6 of BAM with a focus on transport regulations and related testing. The behaviour of primer caps in different packaging configurations is addressed and the new apparatus for the "Minimum Burning Pressure" test is presented. Further topics regarding classification are touched with the aim to attract comments and stimulate cooperation internationally.
Identifying nanomaterials (NMs) according to European Union Legislation is challenging, as there is an enormous variety of materials, with different physico-chemical properties. The NanoDefiner Framework and its Decision Support Flow Scheme (DSFS) allow choosing the optimal method to measure the particle size distribution by matching the material properties and the performance of the particular measurement techniques. The DSFS leads to a reliable and economic decision whether a material is an NM or not based on scientific criteria and respecting regulatory requirements. The DSFS starts beyond regulatory requirements by identifying non-NMs by a proxy Approach based on their volume-specific surface area. In a second step, it identifies NMs. The DSFS is tested on real-world materials and is implemented in an e-tool. The DSFS is compared with a decision flowchart of the European Commission’s (EC) Joint Research Centre (JRC), which rigorously follows the explicit criteria of the EC NM definition with the focus on identifying NMs, and non-NMs are identified by exclusion. The two approaches build on the same scientific basis and measurement methods, but start from opposite ends: the JRC Flowchart starts by identifying NMs, whereas the NanoDefiner Framework first identifies non-NMs.
The safety characteristics of flammable gases and liquids are required when identifying potentially explosive mixtures and taking appropriate actions concerning explosion protection. Examples are given here of the safe handling and evaluation of hazards during the processing, storage, transport, and disposal of flammable liquids and gases. The CHEMSAFE database is presented as a reliable source of safety characteristic data, and its new open-access version is introduced. CHEMSAFE currently contains assessed properties for about 3000 liquids, gases and mixtures. The lack of a broad experimental foundation in the extensive field of non-atmospheric conditions shows the need for further investigation and standardization. This article summarizes experimental evidence and estimation methods for safety characteristic data under non-atmospheric conditions pointing out current limitations. Suggestions for pre-normative research on safety data under non-atmospheric conditions are given.
The safety characteristics of flammable gases and liquids are required when identifying potentially explosive mixtures and taking appropriate actions concerning explosion protection. Examples are given in this review of the safe handling and evaluation of hazards during the processing, storage, transport, and disposal of flammable liquids and gases. The CHEMSAFE database is presented as a reliable source of safety characteristic data, and ist new open-access version is introduced. CHEMSAFE currently contains assessed properties for about 3000 flammable liquids, gases and mixtures. The lack of a broad experimental foundation in the extensive field of non-atmospheric conditions shows the need for further investigation and standardization. This review summarizes experimental evidence and estimation methods for safety characteristic data under non-atmospheric conditions pointing out current limitations. Suggestions for pre-normative research on safety data under nonatmospheric conditions are given.
The safety characteristics of flammable gases and liquids are required when identifying potentially explosive mixtures and taking appropriate actions concerning explosion protection. Examples are given in this review of the safe handling and evaluation of hazards during the processing, storage, transport, and disposal of flammable liquids and gases. The CHEMSAFE database is presented as a reliable source of safety characteristic data, and ist new open-access version is introduced. CHEMSAFE currently contains assessed properties for about 3000 flammable liquids, gases and mixtures. The lack of a broad experimental foundation in the extensive field of non-atmospheric conditions shows the need for further investigation and standardization. This review summarizes experimental evidence and estimation methods for safety characteristic data under non-atmospheric conditions pointing out current limitations. Suggestions for pre-normative research on safety data under nonatmospheric conditions are given.
Polymerizing Substances
(2017)
Polymerizing substances are classified in different classes of the UN Recommendations on the Transport of Dangerous Goods. Based on incidents a new division 4.1 for polymerizing substances, which are not meet the criteria of the Classes 1-8, was implemented in the regulations. In the lecture, the criteria and the determination of the SAPT (self-accelerating polymerization temperature are discussed.