Implementation of a probabilistic based framework for safety assessment of existing timber elements

The assessment of existing timber structures is often limited to information obtained from non or semi destructive testing, as mechanical testing is in many cases not possible due to its destructive nature. Therefore, the available data provides only an indirect measurement of the reference mechanical properties of timber elements, often obtained through empirical based correlations. Moreover, the data must result from the combination of different tests, as to provide a reliable source of information for a structural analysis. Even if general guidelines are available for each typology of testing, there is still a need for a global methodology allowing to combine information from different sources and infer upon that information in a decision process. In this scope, the present work presents the implementation of a probabilistic based framework for safety assessment of existing timber elements. This methodology combines information gathered in different scales and follows a probabilistic framework allowing for the structural assessment of existing timber elements with possibility of inference and updating of its mechanical properties, through Bayesian methods. The probabilistic based framework is based in four main steps: (i) scale of information; (ii) measurement data; (iii) probability assignment; and (iv) structural analysis. In this work, the proposed methodology is implemented in a case study. Data was obtained through a multi-scale experimental campaign made to old chestnut timber beams accounting correlations of non and semi-destructive tests with mechanical properties. Finally, different inference scenarios are discussed aiming at the characterization of the safety level of the elements.

Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

Tensile stress–crack width law for steel fibre reinforced self-compacting concrete obtained from indirect (splitting) tensile tests

In this work, the fracture mode I parameters of steel fibre reinforced self-compacting concrete (SFRSCC) were derived from the numerical simulation of indirect splitting tensile tests. The combined experimental and numerical research allowed a comparison between the stress-crack width (σ - w) relationship acquired straightforwardly from direct tensile tests, and the σ - w response derived from inverse analysis of the splitting tensile tests results. For this purpose a comprehensive nonlinear 3D finite element (FE) modeling strategy was developed. A comparison between the experimental results obtained from splitting tensile tests and the corresponding FE simulations confirmed the good accuracy of the proposed strategy to derive the σ – w for these composites. It is concluded that the post-cracking tensile laws obtained from inverse analysis provided a close relationship with the ones obtained from the experimental uniaxial tensile tests.

Shaking table tests of a two-storey log house

This paper presents the findings of an experimental campaign that was conducted to investigate the seismic behaviour of log houses. A two-storey log house designed by the Portuguese company Rusticasa® was subjected to a series of shaking table tests at LNEC, Lisbon, Portugal. The paper contains the description of the geometry and construction of the house and all the aspects related to the testing procedure, namely the pre-design, the setup, instrumentation and the testing process itself. The shaking table tests were carried out with a scaled spectrum of the Montenegro (1979) earthquake, at increasing levels of PGA, starting from 0.07g, moving on to 0.28g and finally 0.5g. The log house did not suffer any major damage and remained in working condition throughout the entire process. The preliminary analysis of the overall behaviour of the log house is also discussed.

Rockburst laboratory tests database - Application of data mining techniques

Rockburst is characterized by a violent explosion of a block causing a sudden rupture in the rock and is quite common in deep tunnels. It is critical to understand the phenomenon of rockburst, focusing on the patterns of occurrence so these events can be avoided and/or managed saving costs and possibly lives. The failure mechanism of rockburst needs to be better understood. Laboratory experiments are undergoing at the Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUE) of Beijing and the system is described. A large number of rockburst tests were performed and their information collected, stored in a database and analyzed. Data Mining (DM) techniques were applied to the database in order to develop predictive models for the rockburst maximum stress (σRB) and rockburst risk index (IRB) that need the results of such tests to be determined. With the developed models it is possible to predict these parameters with high accuracy levels using data from the rock mass and specific project.

Study of natural ventilation for a modular façade system in wind tunnel tests

Wind tunnel tests are a reliable tool to determine the effect of natural ventilation on buildings. This paper presents results of wind tunnel tests conducted to evaluate the influence of ventilation modules positioning on a façade system. Modules positioning was modified, resulting in different façade configurations. The tests were carried out with the use of a model, varying the position of the ventilation modules in the façade configuration. The cases tested were six ventilation modules positioned below the window-sill (ventilated window-sill), and three ventilation modules positioned above and below the façade. The façade system proposed was movable and interchangeable so that the same basic model could be used to test the possibilities for ventilation. Wind speed measurements were taken inside and outside the model for the different façades configurations to evaluate the best performance in relation to natural ventilation. Singleâ sided and Cross ventilation were considered for wind speed measurements. Results show the use of six ventilation modules positioned below the window-sill, forming "a ventilated window-sill" is the best solution in terms of natural ventilation.

Influence of climate on clinical diagnostic dry eye tests: pilot study

Purpose. To analyze dry eye disease (DED) tests and their consistency in similar nonsymptomatic population samples living in two geographic locations with different climates (Continental vs. Atlantic). Methods. This is a pilot study including 14 nonsymptomatic residents from Valladolid (Continental climate, Spain) and 14 sex-matched and similarly aged residents from Braga (Atlantic climate, Portugal); they were assessed during the same season (spring) of two consecutive years. Phenol red thread test, conjunctival hyperemia, fluorescein tear breakup time, corneal and conjunctival staining, and Schirmer test were evaluated on three different consecutive visits. Reliability was assessed using the intraclass correlation coefficient and weighted kappa (J) coefficient for quantitative and ordinal variables, respectively. Results. Fourteen subjects were recruited in each city with a mean (TSD) age of 63.0 (T1.7) and 59.1 (T0.9) years (p = 0.08) in Valladolid and Braga, respectively. Intraclass correlation coefficient and J values of the tests performed were below 0.69 and 0.61, respectively, for both samples, thus showing moderate to poor reliability. Subsequently, comparisons were made between the results corresponding to the middle and higher outdoor relative humidity (RH) visit in each location as there were no differences in mean temperature (p Q 0.75) despite RH values significantly differing (p e 0.005). Significant (p e 0.05) differences were observed between Valladolid and Braga samples on tear breakup time (middle RH visit, 2.76 T 0.60 vs. 5.26 T 0.64 seconds; higher RH visit, 2.61 T 0.32 vs. 5.78 T 0.88 seconds) and corneal (middle RH, 0.64 T 0.17 vs. 0.14 T 0.10; higher RH, 0.60 T 0.22 vs. 0.0 T 0.0) and conjunctival staining (middle RH, 0.61 T 0.17 vs. 0.14 T 0.08; higher RH, 0.57 T 0.15 vs. 0.18 T 0.09). Conclusions. This pilot study provides initial evidence to support that DED test outcomes assessing the ocular surface integrity and tear stability are climate dependent. Future large-sample studies should support these outcomes also in DED patients. This knowledge is fundamental for multicenter clinical trials. Lack of consistency in diagnostic clinical tests for DED was also corroborated. (Optom Vis Sci 2015;92:e284Ye289)

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.