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Curve Skeleton and Moments of Area Supported Beam Parametrization in Multi-Objective Compliance Structural Optimization
No full textThis work addresses the end-to-end virtual automation of structural optimization up to the derivation of a parametric geometry model that can be used for application areas such as additive manufacturing or the verification of the structural optimization result with the finite element method. A holistic design in structural optimization can be achieved with the weighted sum method, which can be automatically parameterized with curve skeletonization and cross-section regression to virtually verify the result and control the local size for additive manufacturing. is investigated in general. In this paper, a holistic design is understood as a design that considers various compliances as an objective function. This parameterization uses the automated determination of beam parameters by so-called curve skeletonization with subsequent cross-section shape parameter estimation based on moments of area, especially for multi-objective optimized shapes. An essential contribution is the linking of the parameterization with the results of the structural optimization, e.g., to include properties such as boundary conditions, load conditions, sensitivities or even density variables in the curve skeleton parameterization. The parameterization focuses on guiding the skeletonization based on the information provided by the optimization and the finite element model. In addition, the cross-section detection considers circular, elliptical, and tensor product spline cross-sections that can be applied to various shape descriptors such as convolutional surfaces, subdivision surfaces, or constructive solid geometry. The shape parameters of these cross-sections are estimated using stiffness distributions, moments of area of 2D images, and convolutional neural networks with a tailored loss function to moments of area. Each final geometry is designed by extruding the cross-section along the appropriate curve segment of the beam and joining it to other beams by using only unification operations. The focus of multi-objective structural optimization considering 1D, 2D and 3D elements is on cases that can be modeled using equations by the Poisson equation and linear elasticity. This enables the development of designs in application areas such as thermal conduction, electrostatics, magnetostatics, potential flow, linear elasticity and diffusion, which can be optimized in combination or individually. Due to the simplicity of the cases defined by the Poisson equation, no experts are required, so that many conceptual designs can be generated and reconstructed by ordinary users with little effort. Specifically for 1D elements, a element stiffness matrices for tensor product spline cross-sections are derived, which can be used to optimize a variety of lattice structures and automatically convert them into free-form surfaces. For 2D elements, non-local trigonometric interpolation functions are used, which should significantly increase interpretability of the density distribution. To further improve the optimization, a parameter-free mesh deformation is embedded so that the compliances can be further reduced by locally shifting the node positions. Finally, the proposed end-to-end optimization and parameterization is applied to verify a linear elasto-static optimization result for and to satisfy local size constraint for the manufacturing with selective laser melting of a heat transfer optimization result for a heat sink of a CPU. For the elasto-static case, the parameterization is adjusted until a certain criterion (displacement) is satisfied, while for the heat transfer case, the manufacturing constraints are satisfied by automatically changing the local size with the proposed parameterization. This heat sink is then manufactured without manual adjustment and experimentally validated to limit the temperature of a CPU to a certain level
Statistical Characterization of Stress Concentrations along Butt Joint Weld Seams Using Deep Neural Networks
Get PDFIn order to ensure high weld qualities and structural integrity of engineering structures, it is crucial to detect areas of high stress concentrations along weld seams. Traditional inspection methods rely on visual inspection and manual weld geometry measurements. Recent advances in the field of automated measurement techniques allow virtually unrestricted numbers of inspections by laser measurements of weld profiles; however, in order to compare weld qualities of different welding processes and manufacturers, a deeper understanding of statistical distributions of stress concentrations along weld seams is required. Hence, this study presents an approach to statistically characterize different types of butt joint weld seams. For this purpose, an artificial neural network is created from 945 finite element simulations to determine stress concentration factors at butt joints. Besides higher quality of predictions compared to empirical estimation functions, the new approach can directly be applied to all types welded structures, including arc- and laser-welded butt joints, and coupled with all types of 3D-measurement devices. Furthermore, sheet thickness ranging from 1 mm to 100 mm can be assessed
Determination of notch factors for transverse non-load carrying stiffeners based on numerical analysis and metamodeling
Get PDFStress concentration factors (SCFs) at weld toes and weld roots as required for the effective notch stress concept (see [ 1 , 2 ]) are usually computed using finite element analysis (FEA) which requires a certain amount of effort for model generation, the solving process, and postprocessing. Regression functions of many FEAs within given parameter bounds provide the possibility of a fast prediction of SCFs. This paper provides new and accurate regression formulae for the estimation of notch stresses at idealized weld geometries on the basis of multiple linear-elastic FEAs for the transverse stiffener (non-load carrying T-joint) under tension and bending of the load carrying slab. Regression of sampled finite element results has been performed using (a) second-order polynomial regression with coupling terms (PRC) and (b) artificial neural networks (ANN). The presented formulae are compared with several existing estimations of stress concentration factors. The new methods appear to show a higher quality of prognosis as well as apply to significant larger ranges of the geometrical parameters of the weld joint. The formulae presented here for the transverse stiffener add another welded joint to a series of similar surrogate models presented from Munich University of Applied Sciences in earlier publications and made available for use by the web-based tool SCF-Predictor
Fatigue assessment of amplitude-modulated non-stationary random vibration loading
No full textDesigning mechanical structures exposed to random vibration loading compromises the central challenges of defining comprehensive load assumptions and of processing these efficiently in a fatigue assessment. For this matter of statistical load description, frequency-domain methods withhold major advantages. They describe random vibration loading by its power spectral density, which allows drastic data reduction, to conduct efficient response analyses and to derive a statistical description of resulting load spectra. Nevertheless, this procedure is limited to stationary Gaussian loading. Thus, this paper proposes an extension of the frequency-domain approach to a special class of non-stationary loading – amplitude-modulated processes. These consist of a unique vibration state that varies in intensity, which is represented by a modulating signal. This paper develops a methodology to test for amplitude-modulated processes, to derive efficient measures for the intensity variation and to include this behavior in a fatigue assessment carried out in frequency-domain. The full methodology is presented via a set of simulated data
Characterizing non-Gaussian vibration loading using the trispectrum
No full textThis paper addresses the use of higher-order spectra to study the non-Gaussian nature of random vibration loading. Since the power spectral density is only a full description for stationary Gaussian processes, specifying non-Gaussian random vibration loading requires a sophisticated statistical description. In recent research higher-order statistical moments such as skewness and kurtosis have been used to de_ne non-Gaussian properties of vibration loading. However, useful information contained in the spectral representation of these moments is neglected. This paper introduces the trispectrum as a tool for analyzing vibration loading. It is the spectral representation of the fourth-order moment and thus extends the information content of the kurtosis. For demonstration several common methods for generating non-Gaussian loading are reviewed and used to derive loads that reproduce the power spectral density and kurtosis of a real in-service loading. These loads are analyzed using Fatigue Damage Spectra and trispectra to relate structural response behavior to their non-Gaussian nature. The results suggest that the trispectrum is a valuable tool for analyzing and classifying non-Gaussian random loading
Rapid differentiation of Francisella species and subspecies by fluorescent in situ hybridization targeting the 23S rRNA
No full textBackground: Francisella (F.) tularensis is the causative agent of tularemia. Due to its low infectious dose, ease of dissemination and high case fatality rate, F. tularensis was the subject in diverse biological weapons programs and is among the top six agents with high potential if misused in bioterrorism. Microbiological diagnosis is cumbersome and time-consuming. Methods for the direct detection of the pathogen (immunofluorescence, PCR) have been developed but are restricted to reference laboratories.
Results: The complete 23S rRNA genes of representative strains of F. philomiragia and all subspecies of F. tularensis were sequenced. Single nucleotide polymorphisms on species and subspecies level were confirmed by partial amplification and sequencing of 24 additional strains. Fluorescent In Situ Hybridization (FISH) assays were established using species- and subspecies-specific probes. Different FISH protocols allowed the positive identification of all 4 F. philomiragia strains, and more than 40 F. tularensis strains tested. By combination of different probes, it was possible to differentiate the F. tularensis subspecies holarctica, tularensis, mediasiatica and novicida. No cross reactivity with strains of 71 clinically relevant bacterial species was observed. FISH was also successfully applied to detect different F. tularensis strains in infected cells or tissue samples. In blood culture systems spiked with F. tularensis, bacterial cells of different subspecies could be separated within single samples.
Conclusion: We could show that FISH targeting the 23S rRNA gene is a rapid and versatile method for the identification and differentiation of F. tularensis isolates from both laboratory cultures and clinical samples
Entwicklung eines Konzepts für videobasierte Anleitungen für die Technische Redaktion am Beispiel BMW Motorrad : Bachelorarbeit im Studiengang Technische Redaktion und Kommunikation
No full textVideobasierte Anleitungen in Form von How-To-Videos werden immer beliebter. Der Wunsch, sich audiovisuell über sein Produkt zu informieren, steigt stetig (vgl. Bitkom 2017, 27). Um diesen Umstand darzulegen, befasst sich diese Arbeit mit dem internen und externen Nutzen solcher Anleitungen für BMW Motorrad. Ziel ist es ein Konzept zur Erstellung von videobasierten Anleitungen anzufertigen. Zunächst wird anhand didaktischer Kriterien eine Checkliste erstellt. Durch diese ist es möglich, eine konsistente videobasierte Anleitung für die Veröffentlichung auf Youtube zu produzieren. Zur Überprüfung ob videobasierte Anleitungen einen Mehrwert aufweisen, werden sowohl Videos auf Youtube, als auch Handlungsanweisungen in der Betriebsanleitung von BMW Motorrad analysiert. Die Analyse erfolgt anhand eines Kriterienkatalogs. Da dieser sowohl qualitative als auch quantitative Aspekte umfasst wird auf die qualitative Inhaltsanalyse nach Mayring zurückgegriffen. Mithilfe dieser gewonnen Daten, werden Handlungsempfehlungen zur Erstellung von videobasierten Anleitungen für BMW Motorrad ausgesprochen. Diese Arbeit richtet sich an Technische Redakteure und Kommunikationswissenschaftler.Video-based instructions in the form of how-to videos are becoming increasingly popular. The desire to inform oneself audio visually about one´s product is constantly increasing (cf. Bitkom 2017, 27). In order to illustrate this fact, this thesis deals with the internal and external benefits of such manuals for BMW Motorrad. The aim is to develop a concept for the production video-based instructions. First, a checklist is drawn up on the basis of didactic criteria. This makes it possible to produce a consistent video-based instruction for publication on Youtube. To check whether video-based instructions have added value, both videos on Youtube and instructions in the BMW Motorrad operating manual are analyzed. The analysis is based on a catalogue of criteria. As this includes both qualitative and quantitative aspects, the qualitative content analysis according to Mayring is used. With the help of this data, recommendations for action are made for the production of video-based instructions for BMW Motorrad. This essay is aimed at technical writers and communication scientists
