Bonded aerospace repairs under tensile loading: Wet chemical surface treatment and selected environmental conditions

Repair of composite structures and the impact of demanding environmental conditions is a crucial issue for the aircraft industry because of the increasing use of composites in modern aircraft. Consequently, the impact of environmental conditions common for aircraft applications on repair specimens in comparison to nonrepaired specimens is studied. All specimens are produced from a woven carbon fiber-reinforced epoxy-based prepreg. For the repair-specimens, an epoxy-based film adhesive is used for the soft patch repair approach. During the repair process, the surface of the precured prepreg is prepared by a mechanical method (sanding) and an additional chemical functionalization, respectively. Moisture absorption of the repair specimens is independent of the surface preparation method and higher for the repaired than for the nonrepaired specimens. The key influencing environmental conditions for the tensile strength and the failure mode of the repair specimens are elevated temperature testing as well as hot/wet conditioning and conditioning in deionized water. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47506.     

Prozesskette zum stofflichen Recycling von Kunststoffabfällen

The material recycling rate for post-consumer plastic in Austria currently ranges around 25?%, because only post-consumer plastic fractions which are disposed as clean mono-materials are available for material recycling. A significant enhancement of the material recycling rate can be achieved with a process chain consisting of wet mechanical processing and thermochemical conversion. The wet mechanical process step enriches polyolefin and polystyrene from different waste sources, which are used as feedstock for a solvent-based, thermal depolymerisation. Via thermal cracking petrochemical intermediates (i.e. short- and long-chained, aromatic and paraffinic hydrocarbons) are produced, which can be appropriately fed into a conventional crude oil refinery and processed to marketable products. In this way, the material cycle can be closed economically feasible. Both the wet mechanical processing and the thermochemical conversion have been proofed in laboratory scale and are currently transferred to pilot scale.     

The influence of the degree of heterogeneity on the elastic properties of random sphere packings

The macroscopic mechanical properties of colloidal particle gels strongly depend on the local arrangement of the powder particles. Experiments have shown that more heterogeneous microstructures exhibit up to one order of magnitude higher elastic properties than their more homogeneous counterparts at equal volume fraction. In this paper, packings of spherical particles are used as model structures to computationally investigate the elastic properties of coagulated particle gels as a function of their degree of heterogeneity. The discrete element model comprises a linear elastic contact law, particle bonding and damping. The simulation parameters were calibrated using a homogeneous and a heterogeneous microstructure originating from earlier Brownian dynamics simulations. A systematic study of the elastic properties as a function of the degree of heterogeneity was performed using two sets of microstructures obtained from Brownian dynamics simulation and from the void expansion method. Both sets cover a broad and to a large extent overlapping range of degrees of heterogeneity. The simulations have shown that the elastic properties as a function of the degree of heterogeneity are independent of the structure generation algorithm and that the relation between the shear modulus and the degree of heterogeneity can be well described by a power law. This suggests the presence of a critical degree of heterogeneity and, therefore, a phase transition between a phase with finite and one with zero elastic properties.     

High performance computing algorithms for land cover dynamics using remote sensing data

Global and regional land cover studies need to apply complex models on selected subsets of large volumes of multi-sensor and multi-temporal data sets that have been derived from raw instrument measurements using widely accepted pre-processing algorithms. The computational and storage requirements of most of these studies far exceed what is possible on a single workstation environment. We have been pursuing a new approach that couples scalable and open distributed heterogeneous hardware with the development of high performance software for processing, indexing and organizing remotely sensed data. Hierarchical data management tools are used to ingest raw data, create metadata and organize the archived data so as to automatically achieve computational load balancing among the available nodes and minimize input/output overheads. We illustrate our approach with four specific examples. The first is the development of the first fast operational scheme for the atmospheric correction of Landsat Thematic Mapper scenes, while the second example focuses on image segmentation using a novel hierarchical connected components algorithm. Retrieval of the global Bidirectional Reflectance Distribution Function in the red and near-infrared wavelengths using four years (1983 to 1986) of Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land data is the focus of our third example. The fourth example is the development of a hierarchical data organization scheme that allows on-demand processing and retrieval of regional and global AVHRR data sets. Our results show that substantial reductions in computational times can be achieved by the high performance computing technology.     

Effect of muscle,ageing time and modified atmosphere packaging conditions on the colour,oxidative and microbiological stability of packed beef

The objective of this study was to evaluate the influence of two different vacuum ageing times (7 and 14 days) and the impact of the modified atmosphere packaging (MAP) configuration (gas/product ratios: 0.5 and 1 and gas composition: 70% O₂ + 30% CO₂ and 40% O₂ + 30% CO₂ + 30% N₂) on the quality of fresh beef during subsequent storage at 4 °C. For this purpose, three separate experiments were performed. For each experiment, two different muscles (Longissimus dorsi and Biceps femoris) were sampled from four double‐muscled Belgian Blue beef carcasses. Next to colour, also the evolution in microbial load, pH, O₂ and CO₂ in the headspace and lipid oxidation at the meat surface were evaluated. A vacuum ageing for 14 days compared with 7 days resulted in a higher initial microbial load on the day of MAP packaging, which resulted finally in a significantly shorter shelf life. This ageing effect was less pronounced on the colour stability and lipid oxidation of the meat samples. No significant influence of the packaging configuration on any of the analysed parameters (colour, microbial load, pH and lipid oxidation at the meat surface) was observed.     

Optimized state estimation by application of machine learning

The requirements concerning the technical availability as part of the overall equipment effectiveness increase constantly in production nowadays. Unplanned downtimes have to be prevented via efficient methods. Predictive, condition-based maintenance represents a valuable approach for fulfilling these demands, but precise models for state estimation are missing. From the manufacturers’ point of view the challenge consists in wear models with the capability of specifying the correct component’s state as well as providing reliable failure forecasts. Unfortunately, nowadays creation of wear models is based on specific stress tests or design of experiments from the manufacturer. The integration of the production phase or even data feedback and user knowledge does not take place. New potential is promised by cross-cutting technologies from ICT like cloud technologies—in general virtual platform concepts—or approaches of machine learning as enabling technologies. The objective of this paper is to adopt existing algorithms to the new application of condition monitoring in order to evaluate the applicability for automated training of robust wear models. In that context the most commonly used algorithms are described and the reader gets an impression what challenges have to be met when dealing with machine learning. A selection of about ten algorithms with 45 variants is evaluated for four different features within a packaging machine. In the outlook the embedding of the trained model in a cloud architecture is presented.     

Source identification of plant-wide faults based on k nearest neighbor time delay estimation

The identification of plant-wide faults is a very important topic as it enables plant operators to decrease rejections or to increase the product quality. This paper shows a fault propagation approach for this field of interest based on time delay estimation. Due to the fact that the estimation of time delays in multiple-input single-output systems or nonlinear systems is either impossible or very difficult with known methods, a new method based on k nearest neighbor imputation was developed and is validated in this paper theoretically. The effectiveness of the identification algorithm is demonstrated on several simulations and on an industrial hydrocracker plant.     

Digital image correlation analysis and modelling of the strain rate in metal cutting

In the last eight decades, considerable modelling and computational efforts have been made to predict the strain rate during cutting with the aim of optimizing machining processes. However, the validation of these modelling approaches on a local scale remains excessively limited due to the lack of in-situ measurements and the faulty existing quick-stop tests. This work presents the in-process analysis of the strain rate and strain in the primary shear zone using high speed Digital Image Correlation (DIC) techniques. The comparison of measured and computed results shows the suitability of the DIC techniques and the robustness of the modelling approaches.     

The implementation deficits of adaptation and mitigation: green buildings and water security in Amsterdam and Boston

Frameworks of environmental regulations are fundamental yet problematic factors in achieving climate mitigation and adaptation policy goals. Recent theoretical arguments claim the value of general legal frameworks to enable experimentation and contextual adaptation of policies. However, empirical research regarding the effects of both general and specific norms in the practice of urban intervention remains limited. In this article we empirically discern how city governments deal with the tension between control and flexibility in the implementation of urban climate change goals. We argue that policies of adaptation/mitigation face two types of implementation problems: non-adaptive implementation and non-implementation. The first stems from an excessively constraining use of rules, while the second derives from a too general and undefined regulatory framework. Analysing two empirical cases in Amsterdam, Netherlands and Boston, MA, USA, we conclude that there are three elements that affect the way actors deal with these deficits: the level of scale at which regulations are established, the degree of land ownership which provides margin of manoeuvre to public authorities, and the sense of political urgency behind mitigation and adaptation policies.     

Chemical warfare and survival strategies in bacterial range expansions

Dispersal of species is a fundamental ecological process in the evolution and maintenance of biodiversity. Limited control over ecological parameters has hindered progress in understanding of what enables species to colonize new areas, as well as the importance of interspecies interactions. Such control is necessary to construct reliable mathematical models of ecosystems. In our work, we studied dispersal in the context of bacterial range expansions and identified the major determinants of species coexistence for a bacterial model system of three Escherichia coli strains (toxin-producing, sensitive and resistant). Genetic engineering allowed us to tune strain growth rates and to design different ecological scenarios (cyclic and hierarchical). We found that coexistence of all strains depended on three strongly interdependent factors: composition of inoculum, relative strain growth rates and effective toxin range. Robust agreement between our experiments and a thoroughly calibrated computational model enabled us to extrapolate these intricate interdependencies in terms of phenomenological biodiversity laws. Our mathematical analysis also suggested that cyclic dominance between strains is not a prerequisite for coexistence in competitive range expansions. Instead, robust three-strain coexistence required a balance between growth rates and either a reduced initial ratio of the toxin-producing strain, or a sufficiently short toxin range.