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.

Environment, health and safety policy in small construction sites: an analysis of the situation in Brazil

This paper analyzes the safety, environmental and occupational health of workers in the small construction industry in Brazil. In this sector there are still many unsafe practices, which are very common in small work sites. We used a qualitative approach to understand these problems by long interviews with people who work directly in small construction sites, including occupational physicians, civil engineers, safety engineers, safety technicians, general foremen, construction workers, labor unionists and auditors. This paper aims to demonstrate that the "invisibility" of the small sites workers makes them less safe and therefore more prone to accidents, also weakening their health. The results show that small constructions workers are less visible to society and supervision because of their short periods of work. Therefore, they are also uncovered to the rigorous applicability of principles of safety and accident prevention. Thus, it has been seen in this field of work a precarious application of NR - 18, which was specifically made for the construction sites and it needs simplification to meet normative characteristics of small construction sites. In the State of Rio de Janeiro, some laws on small sites were recently created and implemented. This study concludes that the rules to work are not being taken as seriously as the legislation determinates, remaining practically unknown by many professionals, from the plot command, supervisors, engineers, architects and technicians who work on construction sites. This ignorance creates space for the lack of safety and consequently to accidents, leading to by weakness in the workers health. Therefore, the work process needs to be modified, the safety regulation must be disseminated through safer practices, promoting employee health and ensure that the work of small sites can be visible, especially ensuring the construction workers health and safety.

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.

“It’s a complicated situation”. Harm in everyday experiences with technology. A qualitative study with school-aged children

Tese de Doutoramento em Ciências da Educação (Especialidade de Tecnologia Educativa)

Upgrade of an industrial building: BIM model of the as-built situation and evaluation of modifications

Dissertação de mestrado integrado in Civil Engineering

Current situation on the occurrence of mycotoxins and toxigenic fungi in Portugal

Mycotoxins are secondary metabolites produced by filamentous fungi that are toxic for humans and animals in small amounts and that are found worldwide in a large number of agricultural commodities. They are usually ingested involuntarily, when contaminated plant products are consumed, and represent a great risk for public health. Therefore, governments throughout the world have imposed strict legal limits for their levels in food and feed products in order to reduce potential health risks for consumers. Despite of its ubiquity, the mycotoxin problem is mainly dependent on regional factors, such as the mycotoxigenic characteristics of the local mycoflora, the local climate conditions, and the local agricultural practices. For this reason, a constant vigilance from local governmental food safety agencies and from the local researcher community is needed. This communication will review the current situation on the occurrence of mycotoxigenic fungi in some Portuguese cultures, such as wine grapes, corn and dried fruits. Particular attention will be given to the incidence of mycotoxigenic Aspergillus strains in those cultures and to the levels of ochratoxin A, aflatoxins, cyclopiazonic acid and fumonisin B2 produced. Data will be discussed taking into account the geographical origin of the isolates and the particular climate conditions of each sampling region. An updated review on the levels of the main mycotoxins found in local products and in imported commodities will also be presented.

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.