7 resultados para Analysis of the symmetry Lie group and Lie algebra of differential systems
em Universidade do Minho
Resumo:
Timber connections represent the crucial part of a timber structure and a great variability exists in terms of types of connections and mechanisms. Taking as case study the widespread traditional timber frame structures, in particular the Portuguese Pombalino buildings, one of the most common timber connection is the half-lap joint. Connections play a major role in the overall behaviour of a structure, particularly when assessing their seismic response, since damage is concentrated at the connections. For this reason, an experimental campaign was designed and distinct types of tests were carried out on traditional half-lap joints to assess their in-plane response. In particular, pull-out and in-plane cyclic tests were carried out on real scale unreinforced connections. Subsequently, the connections were retrofitted, using strengthening techniques such as self-tapping screws, steel plates and GFRP sheets. The tests chosen were meant to capture the hysteretic behaviour and dissipative capacity of the connections and characterise their response and, therefore, their influence on the seismic response of timber frame walls, particularly concerning their uplifting and rotation capacity, that could lead to rocking in the walls. In this paper, the results of the experimental campaign are presented in terms of hysteretic curves, dissipated energy and equivalent viscous damping ratio. Moreover, recommendations are provided on the most appropriate retrofitting solutions.
Risk acceptance in the furniture sector: Analysis of acceptance level and relevant influence factors
Resumo:
Risk acceptance has been broadly discussed in relation to hazardous risk activities and/or technologies. A better understanding of risk acceptance in occupational settings is also important; however, studies on this topic are scarce. It seems important to understand the level of risk that stakeholders consider sufficiently low, how stakeholders form their opinion about risk, and why they adopt a certain attitude toward risk. Accordingly, the aim of this study is to examine risk acceptance in regard to occupational accidents in furniture industries. The safety climate analysis was conducted through the application of the Safety Climate in Wood Industries questionnaire. Judgments about risk acceptance, trust, risk perception, benefit perception, emotions, and moral values were measured. Several models were tested to explain occupational risk acceptance. The results showed that the level of risk acceptance decreased as the risk level increased. High-risk and death scenarios were assessed as unacceptable. Risk perception, emotions, and trust had an important influence on risk acceptance. Safety climate was correlated with risk acceptance and other variables that influence risk acceptance. These results are important for the risk assessment process in terms of defining risk acceptance criteria and strategies to reduce risks.
Resumo:
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.
Resumo:
The monitoring data collected during tunnel excavation can be used in inverse analysis procedures in order to identify more realistic geomechanical parameters that can increase the knowledge about the interested formations. These more realistic parameters can be used in real time to adapt the project to the real structure in situ behaviour. However, monitoring plans are normally designed for safety assessment and not especially for the purpose of inverse analysis. In fact, there is a lack of knowledge about what types and quantity of measurements are needed to succeed in identifying the parameters of interest. Also, the optimisation algorithm chosen for the identification procedure may be important for this matter. In this work, this problem is addressed using a theoretical case with which a thorough parametric study was carried out using two optimisation algorithms based on different calculation paradigms, namely a conventional gradient-based algorithm and an evolution strategy algorithm. Calculations were carried for different sets of parameters to identify several combinations of types and amount of monitoring data. The results clearly show the high importance of the available monitoring data and the chosen algorithm for the success rate of the inverse analysis process.
Resumo:
NIPE - WP 02/2016
Resumo:
An analysis is presented of events containing jets including at least one b-tagged jet, sizeable missing transverse momentum, and at least two leptons including a pair of the same electric charge, with the scalar sum of the jet and lepton transverse momenta being large. A data sample with an integrated luminosity of 20.3 fb−1 of pp collisions at s√=8 TeV recorded by the ATLAS detector at the Large Hadron Collider is used. Standard Model processes rarely produce these final states, but there are several models of physics beyond the Standard Model that predict an enhanced rate of production of such events; the ones considered here are production of vector-like quarks, enhanced four-top-quark production, pair production of chiral b′-quarks, and production of two positively charged top quarks. Eleven signal regions are defined; subsets of these regions are combined when searching for each class of models. In the three signal regions primarily sensitive to positively charged top quark pair production, the data yield is consistent with the background expectation. There are more data events than expected from background in the set of eight signal regions defined for searching for vector-like quarks and chiral b′-quarks, but the significance of the discrepancy is less than two standard deviations. The discrepancy reaches 2.5 standard deviations in the set of five signal regions defined for searching for four-top-quark production. The results are used to set 95% CL limits on various models.
Resumo:
Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.