Recycled steel fibre reinforced concrete failing in bending and in shear

Recent research is showing that the addition of Recycled Steel Fibres (RSF) from wasted tyres can decrease significantly the brittle behaviour of cement based materials, by improving its toughness and post-cracking resistance. In this sense, Recycled Steel Fibre Reinforced Concrete (RSFRC) seems to have the potential to constitute a sustainable material for structural and non-structural applications. To assess this potential, experimental and numerical research was performed on the use of RSFRC in elements failing in bending and in beams failing in shear. The values of the fracture mode I parameters of the developed RSFRC were determined by performing inverse analysis with test results obtained in three point notched beam bending tests. To assess the possibility of using RSF as shear reinforcement in Reinforced Concrete (RC) beams, three point bending tests were executed with three series of RSFRC beams flexurally reinforced with a relatively high reinforcement ratio of longitudinal steel bars in order to assure shear failure for all the tested beams. By performing material nonlinear simulations with a computer program based on the finite element method (FEM), the applicability of the fracture mode I crack constitutive law derived from the inverse analysis is assessed for the prediction of the behaviour of these beams. The performance of the formulation proposed by RILEM TC 162 TDF and CEB-FIP 2010 for the prediction of the shear resistance of fibre reinforced concrete elements was also evaluated.

Time-dependent flexural behaviour of cracked steel fibre reinforced self-compacting concrete panels

In the present work are described and discussed the results of an extensive experimental program that aims to study the long-term behaviour of cracked steel fibre reinforced self-compacting concrete, SFRSCC, applied in laminar structures. In a first stage, the influence of the initial crack opening level (wcr = 0.3 and 0.5 mm), applied stress level, fibre orientation/dispersion and distance from the casting point, on the flexural creep behaviour of SFRSCC was investigated. Moreover, in order to evaluate the effects of the creep phenomenon on the residual flexural strength, a series of monotonic tests were also executed. It was found that wcr = 0.5 mm series showed a higher creep coefficient comparing to the series with a lower initial crack opening. Furthermore, the creep performance of the SFRSCC was influenced by the orientation of the extracted prismatic specimens regarding the direction of the concrete flow within the cast panel.

Shear strengthening of damaged reinforced concrete beams with hybrid composite plates

This paper aims to evaluate experimentally the potentialities of Hybrid Composite Plates (HCPs) technique for the shear strengthening of reinforced concrete (RC) beams that were previously subjected to intense damage in shear. HCP is a thin plate of Strain Hardening Cementitious Composite (SHCC) reinforced with Carbon Fiber Reinforced Polymer (CFRP) laminates. For this purpose, an experimental program composed of two series of beams (rectangular and T cross section) was executed to assess the strengthening efficiency of this technique. In the first step of this experimental program, the control beams, without steel stirrups, were loaded up to their shear failure, and fully unloaded. Then, these pre-damaged beams were shear strengthened by applying HCPs to their lateral faces by using a combination of epoxy adhesive and mechanical anchors. The bolts were applied with a certain torque in order to increase the concrete confinement. The obtained results showed that the increase of load carrying capacity of the damaged strengthened beams when HCPs were applied with epoxy adhesive and mechanical anchors was 2 and 2.5 times of the load carrying capacity of the corresponding reference beams (without HCPs) for the rectangular and T cross section beam series, respectively. To further explore the potentialities of the HCPs technique for the shear strengthening, the experimental tests were simulated using an advanced numerical model by a FEM-based computer program. After demonstration the good predictive performance of the numerical model, a parametric study was executed to highlight the influence of SHCC as an alternative for mortar, as well as the influence of torque level applied to the mechanical anchors, on the load carrying capacity of beams strengthened with the proposed technique.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Eco-efficient self-compacting concrete with reduced Portland cement content and high volume of fly ash and metakaolin

The eco-efficient, self-compacting concrete (SCC) production, containing low levels of cement in its formulation, shall contribute for the constructions' sustainability due to the decrease in Portland cement use, to the use of industrial residue, for beyond the minimization of the energy needed for its placement and compaction. In this context, the present paper intends to assess the viability of SCC production with low cement levels by determining the fresh and hardened properties of concrete containing high levels of fly ash (FA) and also metakaolin (MK). Hence, 6 different concrete formulations were produced and tested: two reference concretes made with 300 and 500 kg/m3 of cement; the others were produced in order to evaluate the effects of high replacement levels of cement. Cement replacement by FA of 60% and by 50% of FA plus 20% of MK were tested and the addition of hydrated lime in these two types of concrete were also studied. To evaluate the self-compacting ability slump flow test, T500, J-ring, V-funnel and L-box were performed. In the hardened state the compressive strength at 3, 7, 14, 21, 28 and 90 days of age was determined. The results showed that it is possible to produce low cement content SCC by replacing high levels of cement by mineral additions, meeting the rheological requirements for self-compacting, with moderate resistances from 25 to 30 MPa after 28 days.

Detection of dangerous situations using a smart internet of things system

The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.

A spectrum-driven damage Identification technique : application and validation through the numerical simulation of the Z24 Bridge

The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index.

Shear strengthening of reinforced concrete beams with SHCC-FRP panels

Tese de Doutoramento em Engenharia Civil

Creep behaviour of cracked steel fibre reinforced self-compacting concrete laminar structures

Tese de Doutoramento - Civil Engineering

Gd2O3: Eu Nanoparticle-Based Poly(vinylidene fluoride) Composites for Indirect X-ray Detection

Polymer based scintillator composites have been fabricated by combining poly(vinylidene fluoride) (PVDF) and Gd2O3:Eu nanoparticles (50nm). PVDF has been used since it is a flexible and stable binder matrix and highly resistance to thermal and light deterioration. Gd2O3:Eu has been selected as scintillator material due to its wide band gap, high density and suitable visible light yield. The structural, mechanical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. The introduction of Gd2O3:Eu nanoparticles into the PVDF matrix does not influence the morphology of the polymer or the degree of crystallinity. On the other hand, an increase of the Young´s modulus with respect to PVDF matrix is observed for filler contents of 0.1-0.75 wt.%. The introduction of Gd2O3:Eu into the PVDF matrix increases dielectric constant and DC electrical conductivity as well as the visible light yield in the nanocomposite, being this increase dependent upon Gd2O3:Eu content and X-ray input power. In this way, Gd2O3:Eu/PVDF composites shows suitable characteristics to be used as X-ray radiation transducers, in particular for large area applications.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

On line pre-concentration for simultaneous determination of low molecular weight organic acids and inorganic anions in Amazonian river water samples employing ion chromatography with conductivity detection

An ion chromatography procedure, employing an IonPac AC15 concentrator column was used to investigate on line preconcentration for the simultaneous determination of inorganic anions and organic acids in river water. Twelve organic acids and nine inorganic anions were separated without any interference from other compounds and carry-over problems between samples. The injection loop was replaced by a Dionex AC15 concentrator column. The proposed procedure employed an auto-sampler that injected 1.5 ml of sample into a KOH mobile phase, generated by an Eluent Generator, at 1.5 mL min-1, which carried the sample to the chromatographic columns (one guard column, model AG-15, and one analytical column, model AS15, with 250 x 4mm i.d.). The gradient elution concentrations consisted of a 10.0 mmol l-1 KOH solution from 0 to 6.5 min, gradually increased to 45.0 mmol l-1 KOH at 21 min., and immediatelly returned and maintained at the initial concentrations until 24 min. of total run. The compounds were eluted and transported to an electro-conductivity detection cell that was attached to an electrochemical detector. The advantage of using concentrator column was the capability of performing routine simultaneous determinations for ions from 0.01 to 1.0 mg l-1 organic acids (acetate, propionic acid, formic acid, butyric acid, glycolic acid, pyruvate, tartaric acid, phthalic acid, methanesulfonic acid, valeric acid, maleic acid, oxalic acid, chlorate and citric acid) and 0.01 to 5.0 mg l-1 inorganic anions (fluoride, chloride, nitrite, nitrate, bromide, sulfate and phosphate), without extensive sample pretreatment and with an analysis time of only 24 minutes.

Concurrency detection on finish-to-start activity precedence networks

We explore the finish-to-start precedence relations of project activities used in scheduling problems. From these relations, we devise a method to identify groups of activities that could execute concurrently, i.e. activities in the same group can all execute in parallel. The method derives a new set of relations to describe the concurrency. Then, it is represented by an undirected graph and the maximal cliques problem identifies the groups. We provide a running example with a project from our previous studies in resource constrained project cost minimization together with an example application on the concurrency detection method: the evaluation of the resource stress.