Continuous monitoring of concrete mechanical properties since an early age to support construction phasing

The assessment of concrete mechanical properties during construction of concrete structures is of paramount importance for many intrinsic operations. However many of the available non-destructive methods for mechanical properties have limitations for use in construction sites. One of such methodologies is EMM-ARM, which is a variant of classic resonant frequency methods. This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about concrete mechanical properties such as E-modulus and compressive strength. To achieve the aforementioned objective, a set of adaptations to the method have been successfully implemented and tested: (i) the reduction of the beam span; (ii) the use of a different mould material and (iii) a new support system for the beams. Based on these adaptations, a reusable mould was designed to enable easier systematic use of EMMARM. A pilot test was successfully performed under in-situ conditions during a bridge construction.

Innovative method for the continuous monitoring of concrete viscoelastic properties since early ages: concept and pilot experiments

The experimental evaluation of viscoelastic properties of concrete is traditionally made upon creep tests that consist in the application of sustained loads either in compression or in tension. This kind of testing demands for specially devised rigs and requires careful monitoring of the evolution of strains, whereas assuring proper load constancy. The characterization of creep behaviour at early ages offers additional challenges due to the strong variations in viscoelastic behaviour of concrete during such stages, demanding for several testing ages to be assessed. The present research work aims to assist in reducing efforts for continuous assessment of viscoelastic properties of concrete at early ages, by application of a dynamic testing technique inspired in methodologies used in polymer science: Dynamic Mechanical Analyses. This paper briefly explains the principles of the proposed methodology and exhibits the first results obtained in a pilot application. The results are promising enough to encourage further developments.

Monitoring the early stiffness development in epoxy adhesives for structural strengthening

The present work aimed to assess the early-age evolution of E-modulus of epoxy adhesives used for Fibre-Reinforced Polymer (FRP) strengthening applications. The study involved adapting an existing technique devised for continuous monitoring of concrete stiffness since casting, called EMM-ARM (Elasticity Modulus Measurement through Ambient Response Method) for evaluation of epoxy stiffness. Furthermore, monotonic tensile tests according to ISO standards and cyclic tensile tests were carried out at several ages. A comparison between the obtained results was performed in order to better understand the performance of the several techniques in the assessment of stiffness of epoxy resins. When compared to the other methodologies, the method for calculation of E-modulus recommended by ISO standard led to lower values, since in the considered strain interval, the adhesive had a non-linear stress–strain relationship. The EMM-ARM technique revealed its capability in clearly identifying the hardening kinetics of epoxy adhesives, measuring the material stiffness growth during the entire curing period. At very early ages the values of Young׳s modulus obtained with quasi-static tests were lower than the values collected by EMM-ARM, due to the fact that epoxy resin exhibited a significant visco-elastic behaviour.

Fluência no betão desde as primeiras idades: um estudo experimental

Dissertação de mestrado integrado em Engenharia Civil

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

Real-time monitoring of progression towards renal failure in primary care patients

First published online: December 16, 2014.