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.     

Response of Corn Seedlings (Zea mays L.) to Different Concentrations of Nitrogen in Absence and Presence of Silicon

Silicon - Corn plants are highly demanding of nitrogen and the application of silicon has been studied because it minimizes stress from different natures, and for the better utilization of some...     

Suitable Impact Parameters for High-Speed Joining and Influence on the Bonding Zone Microstructure

Welding by electromagnetic forming is an interesting alternative for material combinations which are not suitable for conventional welding by melting. Even though the underlying bonding mechanisms and the right choice of process parameters are thoroughly discussed in the current literature, there is still a lack of target-oriented process dimensioning. The present paper describes the model experiment used for studying the dependencies between bonding quality and design parameters for three material combinations (mild steel, aluminum base alloy, pure titanium). The resulting bonding zones were analyzed by means of optical microscopy and electron probe microanalyses. Limits for the process parameters are described and the results demonstrate increasing bonding qualities for increasing collision energies and collision angles.     

Matrix generation within a macroporous non-degradable implant for osteochondral defects is not enhanced with partial enzymatic digestion of the surrounding tissue: evaluation in an in vivo rabbit model

Articular cartilage defects are a significant source of pain, have limited ability to heal, and can lead to the development of osteoarthritis. However, a surgical solution is not available. To tackle this clinical problem, non-degradable implants capable of carrying mechanical load immediately after implantation and for the duration of implantation, while integrating with the host tissue, may be viable option. But integration between articular cartilage and non-degradable implants is not well studied. Our objective was to assess the in vivo performance of a novel macroporous, nondegradable, polyvinyl alcohol construct. We hypothesized that matrix generation within the implant would be enhanced with partial digestion of the edges of articular cartilage. Our hypothesis was tested by randomizing an osteochondral defect created in the trochlea of 14 New Zealand white rabbits to treatment with: (i) collagenase or (ii) saline, prior to insertion of the implant. At 1 and 3-month post-operatively, the gross morphology and histologic appearance of the implants and the surrounding tissue were assessed. At 3 months, the mechanical properties of the implant were also quantified. Overall, the hydrogel implants performed favorably; at all time-points and in all groups the implants remained well fixed, did not cause inflammation or synovitis, and did not cause extensive damage to the opposing articular cartilage. Regardless of treatment with saline or collagenase, at 1 month post-operatively implants from both groups had a contiguous interface with adjacent cartilage and were populated with chondrocyte-like cells. At 3 months fibrous encapsulation of all implants was evident, there was no difference between area of aggrecan staining in the collagenase versus saline groups, and implant modulus was similar in both groups; leading us to reject our hypothesis. In summary, a porous PVA osteochondral implant remained well fixed in a short term in vivo osteochondral defect model; however, matrix generation within the implant was not enhanced with partial digestion of adjacent articular cartilage.     

Calibration and validation of a solar thermal system model in Modelica

Recent advancements in the domain of modeling physical processes offer opportunities to use equation based modeling environments, such as Modelica, for the simulation of building heating, ventilation, and air-conditioning (HVAC) systems. The current work demonstrates Modelica capabilities in a case study of real building solar thermal system simulation. The simulated system is part of an innovative ENERGYbase building, designed according to the so called Passivhaus standard. Model calibration and validation procedure is developed to include optimization based parametric adjustments of component models using the monitoring data during a single week. The calibrated system adequately reproduces half a year of real system operation. Future work will concentrate on application of the developed calibration and validation methodology in the whole year overall building energy simulation.     

Efficient document image binarization using heterogeneous computing and parameter tuning

In the context of historical document analysis, image binarization is a first important step, which separates foreground from background, despite common image degradations, such as faded ink, stains, or bleed-through. Fast binarization has great significance when analyzing vast archives of document images, since even small inefficiencies can quickly accumulate to years of wasted execution time. Therefore, efficient binarization is especially relevant to companies and government institutions, who want to analyze their large collections of document images. The main challenge with this is to speed up the execution performance without affecting the binarization performance. We modify a state-of-the-art binarization algorithm and achieve on average a 3.5 times faster execution performance by correctly mapping this algorithm to a heterogeneous platform, consisting of a CPU and a GPU. Our proposed parameter tuning algorithm additionally improves the execution time for parameter tuning by a factor of 1.7, compared to previous parameter tuning algorithms. We see that for the chosen algorithm, machine learning-based parameter tuning improves the execution performance more than heterogeneous computing, when comparing absolute execution times.