Structural damage identification via time domain response and Markov Chain Monte Carlo method

The present work addresses the problem of structural damage identification built on the statistical inversion approach. Here, the damage state of the structure is continuously described by a cohesion parameter, which is spatially discretized by the finite element method. The inverse problem of damage identification is then posed as the determination of the posterior probability densities of the nodal cohesion parameters. The Markov Chain Monte Carlo method, implemented with the Metropolis–Hastings algorithm, is considered in order to approximate the posterior probabilities by drawing samples from the desired joint posterior probability density function. With this approach, prior information on the sought parameters can be used and the uncertainty concerning the known values of the material properties can be quantified in the estimation of the cohesion parameters. The assessment of the proposed approach has been performed by means of numerical simulations on a simply supported Euler–Bernoulli beam. The damage identification and assessment are performed considering time domain response data. Different damage scenarios and noise levels were addressed, demonstrating the feasibility of the proposed approach.     

Coupled temperature and moisture effects on the tensile behavior of strain hardening cementitious composites (SHCC) reinforced with PVA fibers

This paper reports the experimental findings on the tensile behavior of strain-hardening cement-based composites (SHCC). The composites were subjected to the combined effects of elevated temperatures and internal moisture condition. Uniaxial tensile tests on dumbbell-shaped SHCC specimens with in situ temperature control were performed at 22, 60 and 100 °C. In addition, the effect of the internal humidity of SHCC (95, 50, 20 and 0%) coupled to the elevated temperatures was investigated. It was shown that the tensile strength decreases and the strain capacity increases with an increase in temperature. The influence of the internal moisture conditions was more significant in high temperatures. The strain capacity reduced significantly with a decrease in the humidity level. The crack pattern of the SHCC specimens was determined. Furthermore, single fiber pullout tests were performed under the considered high temperatures condition. Finally, the results are discussed based on the thermogravimetry analysis of the PVA fiber, alterations on its microstructure and surface coating.     

Microwave-Assisted Fabrication of Superamphiphobic Surfaces on Aluminum Substrates

The field of superamphiphobic surface fabrication has evolved rapidly in the last decade; however, research on important issues such as sustainability and green chemistry procedures is still scarce. Herein, a simple method of microwave irradiation (MW) to minimize energy consumption during the preparation of superamphiphobic aluminum (Al) surfaces is reported. Al substrates are first etched in diluted HCl solutions to generate a microstructure and then irradiated in a commercial microwave unit for several time intervals, temperatures, and pressures. The surfaces are then coated with different compounds, and the wettability is tested with high and very-low surface tension liquids. Optical profilometry and scanning electron microscopy images show that the density of hierarchical micro-nanostructures increases with MW time, temperature, and pressure. At 170 °C and 7.9 bar, the surfaces present a high density of structures and re-entrant topographies. The obtained coatings display excellent repellence to liquids with surface tensions as low as 27.5 mN m⁻¹. X-ray photoelectron spectroscopy data show the importance of efficient surface functionalization for the production of superamphiphobicity in Al substrates. The results show that MW irradiation of Al substrates can be a green and efficient method for fabricating superamphiphobic surfaces.     

Science macro-indicators: some aspects of ost experience

We report OST experience on macro-indicators producing, especially on academic science and ISI sources. This task requires a combination of organizational choices for data handling and processing, and of bibliometric choices for a selection of indicators appropriate to the missions. Both aspects are briefly studied: the OST database, which also contains nonbibliometric datasets, is organized on the relational principle (RDBMS). Bibliometric indicators selected are classical ones, with a stress on overall coherence. In conclusion, standardization issue is briefly discussed. Standardization may not be desirable at the same extent for different targets (data, nomenclatures, indicators, procedures, etc.) and must not hinder further research. Natural process of communication and explication may also lead to fruitful convergences, without freezing supposed best ways.     

Imhotep: an approach to user and device conscious mobile applications

As the dependence on mobile devices increases, the need for supporting a wider range of users and devices becomes crucial. Elders and people with disabilities adopt new technologies reluctantly, a tendency caused by the lack of adaptation of these technologies to their needs. To address this challenge, this paper describes a framework, Imhotep, whose aim is to aid developers in the accessible application creation process, making the creation of user-centered applications easier and faster. Our framework allows to easily adapt the applications to the constraints imposed by the user capabilities (sensorial, cognitive, and physical capabilities) and device capabilities by providing a repository that will manage the compilation and deployment of applications that include a set of preprocessor directives in the source code. These directives are enhanced with concepts that are automatically adjusted to the current trends of mobile devices by using a Fuzzy Knowledge-Eliciting Reasoner. Our final goal is to increase the number of applications targeted to elders and people with disabilities providing tools that facilitate their development. The paper also describes the evaluation of both the accuracy of the fuzzy terms generated for mobile devices and the usability of the proposed platform.     

Non-standard bone simulation: interactive numerical analysis by computational steering

Numerous numerical methods have been developed in an effort to accurately predict stresses in bones. The largest group are variants of the h-version of the finite element method (h-FEM), where low order Ansatz functions are used. By contrast, we3 investigate a combination of high order FEM and a fictitious domain approach, the finite cell method (FCM). While the FCM has been verified and validated in previous publications, this article proposes methods on how the FCM can be made computationally efficient to the extent that it can be used for patient specific, interactive bone simulations. This approach is called computational steering and allows to change input parameters like the position of an implant, material or loads and leads to an almost instantaneous change in the output (stress lines, deformations). This direct feedback gives the user an immediate impression of the impact of his actions to an extent which, otherwise, is hard to obtain by the use of classical non interactive computations. Specifically, we investigate an application to pre-surgical planning of a total hip replacement where it is desirable to select an optimal implant for a specific patient. Herein, optimal is meant in the sense that the expected post-operative stress distribution in the bone closely resembles that before the operation.     

Information versus Communication in Course Management System participation

Web resources in Latin American higher education institutions have been reported to show a much stronger emphasis on Information than on Communication. A Course Management System (CMS), according to Social Constructivism framework, is an opportunity for fostering learning through interaction in a virtual environment for learning; hence, stimulating the use of a CMS for communication purposes seems quite appropriate. A quantitative analysis of 63.06% of the virtual classrooms was conducted, using the users log database to describe five variables: Participation, Informational Interaction Level, Communicational Interaction Level, and the use of Informational Resources and Communicational Resources in the CMS. An assessment of the first 2 years of implementation of Moodle in a campus confirmed prominence levels of interaction and resources that favor Information over Communication purposes in the use of the CMS. It is not conclusive whether this necessarily implies more or better learning; a profound qualitative study would be needed to answer these questions. Teachers and students show different behaviors in the face of this new ICT campus resource, while faculty members appear to have behaved in an erratic manner, students show steady levels of CMS usage.     

Design issue of a new iCub head sub-system

I am presenting a new design for the head sub-system of the humanoid robot iCub. ICub is a humanoid robot platform that has been conceived as a result of the development of the European Project RobotCub. Mechanical problems of the current head sub-system of iCub robot have been studied in order to figure out improvements for a new design. The feasibility of the new design has been checked through dynamic simulations of the head operations. The successful results have shown plots with curve evolutions of smooth shapes and suitable values of important kinematic and dynamic parameters of the head structure.     

Vehicle inductive signatures recognition using a Madaline neural network

In this paper, we report results obtained with a Madaline neural network trained to classify inductive signatures of two vehicles classes: trucks with one rear axle and trucks with double rear axle. In order to train the Madaline, the inductive signatures were pre-processed and both classes, named C2 and C3, were subdivided into four subclasses. Thus, the initial classification task was split into four smaller tasks (theoretically) easier to be performed. The heuristic adopted in the training attempts to minimize the effects of the input space non-linearity on the classifier performance by uncoupling the learning of the classes and, for this, we induce output Adalines to specialize in learning one of the classes. The percentages of correct classifications presented concern patterns which were not submitted to the neural network in the training process, and, therefore, they indicate the neural network generalization ability. The results are good and stimulate the maintenance of this research on the use of Madaline networks in vehicle classification tasks using not linearly separable inductive signatures.     

Control of absorption columns in the bioethanol process: Influence of measurement uncertainties

The alcohol lost by evaporation during the bioethanol fermentation process may be collected and recovered using an absorption column. This equipment is also used in the carbonic gas treatment, a by-product from the sugar cane fermentation. In the present work, the development of nonlinear feedforward–feedback controllers, based on neural network inverse models, was proposed and tested to manipulate the absorbent flow rates. The control purposes are: to keep low ethanol concentration in the effluent gas phase from the first absorption column (ethanol recovery column); and to reduce the residual water concentration in the CO₂ gas effluent from the second tower (CO₂ treatment column).Based on simulation studies, the neural network (ANN) controller performance was compared with the conventional PID control scheme application. The best ANN architecture was set up according to the Foresse and Hagan (1997) criterion, while the PID parameters were found from the well-known Cohen–Coon Equations and trial-and-error fine tuning.Initially, performances were evaluated for the system without concentration measurement uncertainties. From these tests, the ANN controller presented the smallest response time and overshoot for regulator and servo problems. Three uncertainty levels were applied afterwards: 5%, 10%, and 15%.The ANN controller outperformed the PID for all uncertainty levels tested for the ethanol recovery column. For the CO₂ treatment column, the ANN controller proceeded successfully under uncertainties of 5% and 10%, while the PID did not deal properly with uncertainties above 5%. The statistical F-test, besides the ITAE, ISE, and IAE performance criteria, were calculated for both controllers applications and then compared. They proved the superiority of the ANN control scheme.Using appropriately the proposed well-controlled absorption columns increases the efficiency of the bioethanol production plant and can also provide carbon credits by avoiding CO₂ emission into the atmosphere.