Assessment of cumulative damage by using ultrasonic C-scan on carbon fiber/epoxy composites under thermal cycling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Experimental damage detection grammian matrix

Structural Health Monitoring (SHM) has diverse potential applications, and many groups work in the development of tools and techniques for monitoring structural performance. These systems use arrays of sensors and can be integrated with remote or local computers. There are several different approaches that can be used to obtain information about the existence, location and extension of faults by non destructive tests. In this paper an experimental technique is proposed for damage location based on an observability grammian matrix. The dynamic properties of the structure are identified through experimental data using the eigensystem realization algorithm (ERA). Experimental tests were carried out in a structure through varying the mass of some elements. Output signals were obtained using accelerometers.

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

Damage Detection in Flexible Plate Using Lamb Waves

This paper presents an experimental technique for structural health monitoring (SHM) based on Lamb waves approach in an aluminum plate using piezoelectric material as actuators and sensors. Lamb waves are a form of elastic perturbation that remains guided between two parallel free surfaces, such as the upper and lower surfaces of a plate, beam or shelf. Lamb waves are formed when the actuator excites the surface of the structure with a pulse after receiving a signal. Two PZTs were placed in the plate surface and one of them was used to send a predefined wave through the structure. Thus, the other PZT (adjacent) becomes the sensor. Using this methodology, this paper presents one case of damage detection considering the aluminum plate in the free-free-free-free boundary condition. The damage was simulated by adding additional mass on the plate. It is proposed two damage detection indexes obtained from the experimental signal, involving the Fast Fourier Transform (FFT) and the power spectral density (PSD) that were computed using the output signal. The results show the viability of the presented methodology to damage detection in smart structures

Structural damage identification and location using grammian matrices

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DNA damage in patients who underwent minimally invasive surgery under inhalation or intravenous anesthesia

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation of DNA damage and lipoperoxidation of propofol in patients undergoing elective surgery

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Lower levels of oxidative DNA damage and apoptosis in lymphocytes from patients undergoing surgery with propofol anesthesia

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relationships between cagA, vacA, and iceA genotypes of Helicobacter pylori and DNA damage in the gastric mucosa

Helicobacter pylori (H. pylori) is believed to dispose carriers to gastric cancer by inducing chronic inflammation. The inflammatory processes may result in the generation of reactive oxygen and nitrogen species that damage DNA. In this study, we investigated the relationships between DNA damage in the gastric mucosa and cogA, vocA, and iceA genotypes of H. pylori. The study was conducted with biopsies from the gastric antrum and corpus of 98 H. pylori-infected and 26 uninfected control patients. H. pylori genotypes were determined by PCR and DNA damage was measured in gastric mucosal cells by the Comet assay (single cell gel electrophoresis). All patients were nonsmokers, not abusing alcohol, and not using prescription or recreational drugs. Levels of DNA damage were significantly higher (P < 0.0001) in the H. pylori-infected patients than in uninfected patients. In comparison with the level of DNA damage in the uninfected controls, the extent of DNA damage in both the antrum (OR = 8.45; 95% Cl 2.33-37.72) and the corpus (OR 6.55; 95% Cl 2.52-17.72) was related to infection by cagA(+)/vocAs1m1 and iceA1 strains. The results indicate that the genotype of H. pylori is related to the amount of DNA damage in the gastric mucosa. These genotypes could serve as biomarkers for the risk of extensive DNA damage and possibly gastric cancer. (C) 2004 Wiley-Liss, Inc.

Relationship among oxidative DNA damage, gastric mucosal density and the relevance of cagA, vacA and iceA genotypes of Helicobacter pylori

The aim of this study was to evaluate the relationship among oxidative DNA damage, density of Helicobacter pylori and the relevance of cagA, vacA and iceA genotypes of H. pylori. Gastric epithelial cells were isolated from 24 uninfected patients, 42 H. pylori infected patients with gastritis, and 61 patients with gastric cancer. Oxidative DNA damage was analyzed by the Comet assay, the density of H. pylori was measured by real-time polymerase chain reaction (PCR), and allelic variants of cagA, vacA and iceA were identified using the PCR. Infected patients by Helicobacter pylori cagA(+), vacAs1 m1 and iceA1 genotype showed higher levels of oxidative DNA damage than infected patients with H. pylori cagA(-), vacAs2 m2 and iceA2 genotypes and uninfected patients. Density of H. pylori did not influence oxidative DNA damage. Our results indicate that H. pylori genotype is more relevant than density for oxidative DNA damage.

AT1-receptor mediated vascular damage in myocardium, kidneys and liver in rats

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)