EM - Escola de Minas

URI permanente desta comunidadehttp://www.hml.repositorio.ufop.br/handle/123456789/6

Notícias

A Escola de Minas de Ouro Preto foi fundada pelo cientista Claude Henri Gorceix e inaugurada em 12 de outubro de 1876.

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Resultados da Pesquisa

Agora exibindo 1 - 2 de 2
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    A dual search‐based EPR with self‐adaptive ofspring creation and compromise programming model selection.
    (2021) Gomes, Guilherme José Cunha; Gomes, Ruan Gonçalves de Souza; Vargas Júnior, Eurípedes do Amaral
    Evolutionary polynomial regression (EPR) is extensively used in engineering for soil properties modeling. This grey-box technique uses evolutionary computing to produce simple, transparent and well-structured models in the form of polynomial equations that best explain the observed data. A key task is then to determine mathematical structures for modeling physical phenomena and to select the optimal EPR model. This requires an algorithm to search through the model structure space and successfully produce feasible solutions that honor a set of statistical metrics. The complexity of EPR models increases greatly, however, with the number of polynomial terms used to tune these models. In this paper, we propose an alternative EPR for modeling complex soil properties. We implement a dual search-based EPR with self-adaptive ofspring creation as model structure search strategy and couple a compromise programming tool to select a model that is preferred statistically relative to models with diferent polynomial terms. We illustrate our method using real-world data to improve predictions of optimal moisture content and creep index for soils. Our results demonstrate that the models derived using the proposed methodology can predict soil properties with adequate accuracy, physical meaning and lower number of parameters and input variables.
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    A sustainability-oriented framework for the application of industrial byproducts to the base layers of low-volume roads.
    (2021) Gomes, Guilherme José Cunha; Magalhães, Adair José de; Rocha, Fabiano Lucindo Lima da; Fonseca, Alberto de Freitas Castro
    Roadway engineering works typically rely on the utilization of natural aggregates as building materials. However, growing pressures for sustainable roads are highlighting the importance of replacing virgin materials with industrial byproducts. Constructors worldwide are trying to select optimum soilbyproduct mixtures that have a fair trade-off between engineering properties, environmental impacts and material costs. This requires a multi-objective analysis to explore feasible mixtures that honor a set of preferences to mathematically identify the best compromised soil-byproduct mixture. In this paper, a sustainability-oriented framework is proposed for selecting optimum soil-byproduct proportions for unbound base layers of unpaved roads. A compromise programming tool is implemented to select a mixture that is statistically preferred over mixtures with different byproduct contents. The method is illustrated using technical, economic and environmental indicators that are easily measurable. Investigations are performed for different decision-making perspectives including the constructor’s, contractor’s and the environment’s viewpoints. Two byproducts from the steel industry are mixed in different proportions from 50% to 80% by weight with a clayey soil. The optimum mixture was obtained at a proportion of 70% byproduct and 30% clay. Monte Carlo simulations and sensitivity analysis of transport scenarios further supported this conclusion. Results demonstrate that mixture selection based only on strength properties provides inadequate optimum from a sustainable standpoint. The proposed framework can help road constructors incorporate environmentally-friendly materials in a cost-effective way, while maintaining the technical quality of base layers.