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Woven piezoelectric sensors as part of the textile reinforcement of fiber reinforced plastics
(2019)
Sensor integration in fiber reinforced plastic (FRP) structures enables online process and structural health monitoring (SHM). This paper describes the development and application of woven fabric-based piezoelectric impact and bending sensors for integration into FRP. The work focuses on design and characterization of woven piezoelectric sensors, especially as a part of the reinforcement structure. The reinforcement of the component acts as a sensor in itself and therefore no additional external objects in the form of sensor components or sensor fibers, which could create unwanted weak points within the FRP, are added. The bending test results reveal a direct relationship between the applied load and the sensor signal. Furthermore, the appropriate sensor position in the component cross section was determined and the influence of thermal polarization on the sensor properties was investigated.
In addition to increased safety by detecting possible overload, continuous component monitoring by sensor integration makes the use of fiber reinforced plastics more cost-effective. Since the components are continuously monitored, one can switch from time-based to condition-based maintenance. However, the integration of conventional sensor components causes weak points, as foreign objects are inserted into the reinforcing structure. In this paper, we examine the use of the textile reinforcement as a sensor in itself. We describe how bending sensors can be formed by slightly modifying in the composite’s reinforcement structure. We investigated two different sensor principles. (1) The integration of textile plate capacitors into the structure; (2) The construction of textile piezo elements as part of the reinforcing structure. The bending test results reveal that textile plate capacitors show a load-dependent signal output. The samples with textile piezo elements show a significant increase in signal strength.
In spite of many studies, knowledge about the fundamental factors influencing adhesion between addition curing silicones and aluminum substrates is very limited. The aim of this publication is to evaluate the influence of the formulation and the surface state of the adherend on bond strength. For this purpose, the composition of an addition curing silicone was systematically varied and the effects on both material and bond properties were examined. Additionally, the influence of surface aging at different humidities (0% r. h., 34% r. h., 82% r. h.) of acid etch pretreated aluminum substrates was considered. It is shown that the mechanical properties of the silicone material can be easily adjusted over a wide range by changing the formulation. Although high tensile strengths up to 9.2 MPa for the silicone material can be achieved, lap-shear strengths remain moderate at approximately 3.5 MPa. Predominant adhesive failures show the limited adhesive strength of the basic formulation without additives. Basic ingredients of addition curing silicones without additives are able to reach a certain adhesive strength. However, this strength was quite limited and adhesion promoters are required to further improve adhesion. The humidity at which the pretreated substrates are stored has an overall minor influence on bond strength. Surprisingly, bond strength tends to increase with the storage time of aluminum substrates despite lower surface energies in comparison to freshly pretreated substrates. All in all, the storage conditions of aluminum had a rather small influence on adhesion, whereas the composition of the silicone adhesive strongly influences bond strength.
Digitalization changes the manufacturing dramatically. In regard of employees’ demands, global trends and the technological vision of future factories, automotive manufacturing faces a huge number of diverse challenges. Currently, research focuses on technological aspects of future factories in terms of digitalization. New ways of work and new organizational models for future factories have not been described yet. There are assumptions on how to develop the organization of work in a future factory but up to now, literature shows deficits in scientifically substantiated answers in this research area. Consequently, the objective of this paper is to present an approach on a work organization design for automotive Industry 4.0 manufacturing. Future requirements were analyzed and deducted to criteria that determine future agile organization design. These criteria were then transformed into functional mechanisms, which define the approach for shopfloor organization design
In vitro models of human adipose tissue may serve as beneficial alternatives to animal models to study basic biological processes, identify new drug targets, and as soft tissue implants. With this approach, we aimed to evaluate adipose-derived stem cells (ASC) and mature adipocytes (MA) comparatively for the application in the in vitro setup of adipose tissue constructs to imitate native adipose tissue physiology. We used human primary MAs and human ASCs, differentiated for 14 days, and encapsulated them in collagen type I hydrogels to build up a three-dimensional (3D) adipose tissue model. The maintenance of the models was analyzed after seven days based on a viability staining. Further, the expression of the adipocyte specific protein perilipin A and the release of leptin and glycerol were evaluated. Gene transcription profiles of models based on dASCs and MAs were analyzed with regard to native adipose tissue. Compared to MAs, dASCs showed an immature differentiation state. Further, gene transcription of MAs suggests a behavior closer to native tissue in terms of angiogenesis, which supports MAs as preferred cell type. In contrast to native adipose tissue, genes of de novo lipogenesis and tissue remodeling were upregulated in the in vitro attempts.
On-chip metallization, especially in modern integrated BCD technologies, is often subject to high current densities and pronounced temperature cycles due to heat dissipation from power switches like LDMOS transistors. This paper continues the work on a sensor concept where small sense lines are embedded in the metallization layers above the active area of a switching LDMOS transistor. The sensors show a significant resistance change that correlates with the number of power cycles. Furthermore, influences of sense line layer, geometry and the dissipated energy are shown. In this paper, the focus lies on a more detailed analysis of the observed change in sense line resistance.
Today, virtualizing pharma R&D is increasingly related with data analytics and artificial intelligence (AI), technologies that have been developed by software companies outside the healthcare sector. The process of virtualizing pharma R&D is closely related to the technological advancements that result in the generation of large data sets ranging from genomics, proteomics, metabolomics, medical imaging, IoT wearables and large clinical trials, making it necessary for pharma companies to find new ways to store and ultimately analyze information. As a consequence, pharma companies are experimenting with AI in R&D ranging from in-silico drug design to clinical trail participants identification or dosage error reduction.
Mystery shopping (MS) is a widely used tool to monitor the quality of service and personal selling. In consultative retail settings, assessments of mystery shoppers are supposed to capture the most relevant aspects of sales people’s service and sales behavior. Given the important conclusions drawn by managers from MS results, the standard assumption seems to be that assessments of mystery shoppers are strongly related to customer satisfaction and sales performance. However, surprisingly scant empirical evidence supports this assumption. We test the relationship between MS assessments and customer evaluations and sales performance with large-scale data from three service retail chains. Surprisingly, we do not find asubstantial correlation. The results show that mystery shoppers are not good proxies for real customers. While MS assessments are not related to sales, our findings confirm the established correlation between customer satisfaction measurements and sales results.
Model-based hearing diagnosis based on wideband tympanometry measurements utilizing fuzzy arithmetic
(2019)
Today's audiometric methods for the diagnosis of middle ear disease are often based on a comparison of measurements with standard curves that represent the statistical range of normal hearing responses. Because of large inter-individual variances in the middle ear, especially in wideband tympanometry (WBT), specificity and quantitative evaluation are greatly restricted. A new model-based approach could transform today's predominantly qualitative hearing diganostics into a quantitative and tailored, patient-specific diagnosis, by evaluating WBT measurements with the aid of a middle-ear model. For this particular investigation, a finite element model of a human ear was used. It consisted of an acoustic ear canal and a tympanic cavity model, a middle-ear with detailed nonlinear models of the tympanic membrane and annular ligament, and a simplified inner-ear model. This model has made it possible to identify pathologies from measurements, by analyzing the parameters through senstivity studies and parameter clustering. Uncertainties due to the lack of knowledge, subjectivity in numerical implementation and model simplification are taken into account by the application of fuzzy arithmetic. The most confident parameter set can be determined by applying an inverse fuzzy method on the measurement data. The principle and the benefits of this model-based approach are illustrated by the example of a two-mass oscillator, and also by the simulation of the energy absorbance of an ear with malleus fixation, where the parameter changes that are introduced can be determined quantitatively through the system identification.
Homogeneous and monodispersed furan functionalised melamine-formaldehyde particles were produced. As a precursor, 2-chloro-1,3,5-triazine-2,4-diamine (Mel) was selectively substituted with 2-aminomethyl furan (Fu) units in a convenient one step reaction. The pure reaction product Fu-Mel, which was used without further purification, was reacted with formaldehyde by conventional sol-gel condensation in aqueous medium to yield chemically homogenous, spherically shaped and monodispersed particles. The particles were analysed using ATR-FT-IR, Raman, 1H and 13C NMR spectroscopy, TGA, SEM and DSC measurements. The reactivity of the furan groups located at the particle surface was studied by performing a thermoreversible Diels-Alder cycloaddition reaction with bis-maleimide coupling agents. The formed networks showed thermoreversible behaviour, which was characterised by dynamic IR and DSC measurements.