ALBERT

Description: A new method for the synthesis of structures with prescribed target natural frequencies and mode shapes is presented. The introduction of a modal Rayleigh quotient approximation based on the target mode shapes is the means to propose a structural synthesis problem whose solution is free from eigenvector sensitivity analysis. The frequencies and mode shapes can be adjusted as close as possible to the desired target values, while minimizing the total mass. Several examples corroborate the efficacy of the proposed method.

Description: The paper presents a structural health monitoring system based on propagation of tuned Lamb waves and their interference with discontinuities. The dispersion curves are studied to determine the appropriate type and dimension of transducers and to select the optimum scanning frequencies and relevant propagation modes. A piezoelectric sensor network was implemented in an aluminum plate in order to generate and to sense the wave propagation and associated reflections. The algorithm developed for damage detection relies on the comparison of undamaged and damaged responses of the structure. Combinations of filters and statistical methods were applied to detect differences in the sensor signals acquired for the two different states (damaged and undamaged), corresponding to damage reflections. In order to eliminate the false positives due to noise, a probability analysis is performed to obtain the final damage position. The software designed for the current application allows the automatic calculation of dispersion curves, it executes the scans, performs data processing, executes the detection algorithm and presents the probable damages and their positions in a graphical form. Experiments were performed with the introduction of cumulative damages in the plate such as surface and through-the-thickness holes and cuts, ranging from 7 mm to 1 mm in diameter. Additionally, a stringer was attached to the plate by a single rivet line to simulate an aircraft skin structure. Cuts originating from rivet holes and connecting adjacent rivets, as well as loosened rivets were detected by the system. The introduction of the stringer resulted in a loss of precision in the determination of the radial position of the damages near it. Also, the network revealed significant difficulties in the detection of damages beyond the stringer.

Description: Lamb wave based structural health monitoring shows a lot of potential for damage detection of composite structures. However, currently there is no agreement upon optimal network arrangement or detection algorithm. The objective of this research is to develop a sparse network that can be expanded to detect damage over a large area. To achieve this, a novel technique based on damage progression history has been developed. This technique gives an amplification factor to data along actuator-sensor paths that show a steady reduction in transmitted power as induced damage progresses and is implemented with the reconstruction algorithm for probabilistic inspection of damage (RAPID) technique. Two damage metrics are used with the algorithm and a comparison is made to the more commonly used signal difference coefficient (SDC) metric. Best case results show that damage is detected within 12 mm. The algorithm is also run on a more sparse network with no damage detection, therefore indicating that the selected arrangement is the most sparse arrangement with this configuration.

Description: A predictive control strategy in conjunction with semiactive control algorithms is proposed for damping control of base-isolated structures employing semiactive fluid dampers when subjected to earthquake loads. The controller considers the delays resulting from the device’s dynamics and an observer for state estimation. Twenty artificial accelerograms were generated according to the Eurocode 8 for the Portuguese territory and considered for the numerical simulations of the base-isolated structure representative model. The results of a parametric study on a single degree of freedom model provide an indication for controller design in this type of problems. To evaluate the effectiveness of the proposed strategies, the response of a 10-storey base-isolated dual frame-wall building employing semiactive systems is compared with the original, passive solution and with an earlier proposed optimal controller for this type of problems. It is shown that a well-tuned controller could outperform the original structure, the structural system with a passive device (optimized) as well as with the semiactive optimal controller, in terms of relative displacement and absolute acceleration reductions.

Description: This paper discusses the development of analytical models for the prediction of aircraft cabin noise induced by the external turbulent boundary layer (TBL). While, in previous works, the contribution of an individual panel to the cabin interior noise was considered, here, the simultaneous contribution of multiple flow-excited panels is analyzed. Analytical predictions are presented for the interior sound pressure level (SPL) at different locations inside the cabin of a Blended Wing Body (BWB) aircraft, for the frequency range 0–1000 Hz. The results show that the number of vibrating panels significantly affects the interior noise levels. It is shown that the average SPL, over the cabin volume, increases with the number of vibrating panels. Additionally, the model is able to predict local SPL values, at specific locations in the cabin, which are also affected with by number of vibrating panels, and are different from the average values.

Description: Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.

Description: Essential and nonessential heavy metals like iron (Fe), nickel (Ni), manganese (Mn), zinc (Zn), copper (Cu), cadmium (Cd), chromium (Cr), and lead (Pb) were analyzed in four selected medicinal plants such asCapparis spinosa, Peganum harmala, Rhazya stricta,andTamarix articulataby flame atomic absorption spectrophotometer (FAAS). These medicinal plants are extensively used as traditional medicine for treatment of various ailments by local physicians in the area from where these plants were collected. The concentration level of heavy metals in the selected plants was found in the decreasing order as Fe 〉 Zn 〉 Mn 〉 Cu 〉 Ni 〉 Cr 〉 Cd 〉 Pb. The results revealed that the selected medicinal plants accumulate these elements at different concentrations. Monitoring such medicinal plants for heavy metals concentration is of great importance for physicians, health planners, health care professionals, and policymakers in protecting the public from the adverse effects of these heavy metals.