Composite slabs with reinforced concrete and cold-formed profiled steel deck are very popular and reduce the building construction time. The steel deck acts as a permanent formwork to the
Polydimethylsiloxane (PDMS) is one of the most popular elastomers and has been used in different fields, especially in biomechanics research. Among the many interesting features of this material, its hyperelastic behavior stands out, which allows the use of PDMS in various applications, like the ones that mimic soft tissues. However, the hyperelastic behavior is not linear and needs detailed analysis, especially the characterization of shear strain. In this work, two approaches, numerical and experimental, were proposed to characterize the effect of shear strain on PDMS. The experimental method was implemented as a simple shear testing associated with 3D digital image correlation and was made using two specimens with two thicknesses of PDMS (2 and 4 mm). A finite element software was used to implement the numerical simulations, in which four different simulations using the Mooney–Rivlin, Yeoh, Gent, and polynomial hyperelastic constitutive models were performed. These approaches showed that the maximum value of shear strain occurred in the central region of the PDMS, and higher values emerged for the 2 mm PDMS thickness. Qualitatively, in the central area of the specimen, the numerical and experimental results have similar behaviors and the values of shear strain are close. For higher values of displacement and thicknesses, the numerical simulation results move further away from experimental values.
A small number of individuals infected within a community can lead to the rapid spread of the disease throughout that community, leading to an epidemic outbreak. This is even more true for highly contagious diseases such as COVID-19, known to be caused by the new coronavirus SARS-CoV-2. Mathematical models of epidemics allow estimating several impacts on the population and, therefore, are of great use for the definition of public health policies. Some of these measures include the isolation of the infected (also known as quarantine), and the vaccination of the susceptible. In a possible scenario in which a vaccine is available, but with limited access, it is necessary to quantify the levels of vaccination to be applied, taking into account the continued application of preventive measures. This work concerns the simulation of the spread of the COVID-19 disease in a community by applying the Monte Carlo method to a Susceptible-Exposed-Infective-Recovered (SEIR) stochastic epidemic model. To handle the computational effort involved, a simple parallelization approach was adopted and deployed in a small HPC cluster. The developed computational method allows to realistically simulate the spread of COVID-19 in a medium-sized community and to study the effect of preventive measures such as quarantine and vaccination. The results show that an effective combination of vaccination with quarantine can prevent the appearance of major epidemic outbreaks, even if the critical vaccination coverage is not reached.
abstract:The relationship between a country's level of activity in the construction industry and its stage of economic development is a complex one. Several studies over the last forty years, based mainly on cross sectional data, found a positive association between national income and several measures of the construction industry activity. early studies were concerned with the role of the construction sector, as part of physical capital, in the promotion of economic growth and development. a dominant paradigm that later emerged is the 'Bon curve' or the inverted U-shaped pattern of development. More recent research, based on longitudinal analysis, has also pointed to the non-linear relationship between the share of construction in GDP and the level of income per capita. Using time-series data drawn from the United nations, this study applies an econometric methodology to assess the validity of the underlying propositions in a low-middle income economy-Cape Verde -over the long period of 38 years. The findings are in line with the assumptions that in the upward growth trend in developing countries, the pattern of the construction industry tends to follow that of the general economy.
The fire resistance of composite slabs with steel decking, in Europe, is usually defined using simple calculation models provided by the Eurocode EN 1994-1-2. For assessing the methodology of these simple calculation methods, a new advanced calculation method is presented, using the software ANSYS. The numerical model is first validated with experimental data reported on bibliography and then a parametric analysis is conducted to better understand the effect of the load level on the composite structure under fire. The validation of the simulations consisted of three different models: the first model considers perfect contact between the steel deck and the concrete topping, and the two following models consider the existence of an air gap between these materials, acting as a thermal resistance on the temperature field through the thickness of the slab. The numerical results show good approximation to the experimental results, mainly when using the non-perfect contact model, reaching 3.88% and 16.91% of difference with respect to the insulation and load-bearing criteria, respectively. Based on the validation models, a parametric study is presented, modifying the load level from 10% up to 75%. New simple calculation models are presented to define the fire resistance of composite slabs, considering the load level, and the debonding effect between the concrete and the steel deck.
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