통합 검색 | Korea Science

DE ARAUJO, Victor;POLANCO, Cesar;MORALES, Elen;CORTEZ-BARBOSA, Juliana;GAVA, Maristela;GARCIA, Jose
- Journal of the Korean Wood Science and Technology
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- 제47권5호
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- pp.607-616
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- 2019
On account of the lack of education of Brazilian worker, this paper analyzed the characteristics of those professionals working in the production sector of timber houses. A sectoral survey was carried out with respective entrepreneurs to investigate the available professionals (career and contract types), evaluate the demands of skilled workers, and indicate solutions to improve the quality of labor qualification. Similarly, over 65% of sampled producers presented both direct-hired and outsourced workforce. For such contract ways, Civil Engineers and Architects were the main careers. Carpenters, Civil Engineers and Architects experienced on timber were the main sectoral demands. Timber Engineers have good potentials of service for this sector. The creation of courses on timber products can emerge as a key alternative to train people.
https://doi.org/10.5658/WOOD.2019.47.5.607 인용 PDF KSCI

Lee, Jae-Ho;Akutagawa, Shnichi;Moon, Hong-Duk;Han, Heui-Soo;Yoo, Ji-Hyeung;Kim, Kwang-Yeun
- 한국암반공학회:학술대회논문집
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- 한국암반공학회 2008년도 국제학술회의
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- pp.43-51
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- 2008
Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.
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