Developing a micro-macromechanical approach for evaluating long-term creep in composite cylinders
THIN-WALLED STRUCTURES
Authors: Rafiee, Roham; Ghorbanhosseini, Amin
Abstract
In most industries, composite materials have dominated the market compared with traditional materials and structures, due to their unique properties. Composite structures are usually subjected to long-term loading and experience creep phenomenon. In this study, an integrated modeling for evaluating long-term creep in cylindrical composite structures under constant loading is developed. The modeling procedure is performed at two levels of micro and macro comprising four distinct stages as modeling stress analysis at macro level, long-term creep analysis in pure resin, stress analysis at micro level for extending creep behavior of resin to lamina and updating constitutive relations of each layer. The modeling is in need of short-term creep tests on pure resin as input data and the long-term creep of the composite structure is evaluated for a period of 10,000 h as the output of the modeling. The developed modeling is validated on the basis of a long-term empirical study on a composite pipe subjected to compressive transverse loading. The very good agreement between experimental data and theoretical modeling is observed.
Modeling and Forecasting of Socio-Economic Development of St.Petersburg Region
EDUCATION EXCELLENCE AND INNOVATION MANAGEMENT THROUGH VISION 2020
Authors: Shvetsov, Konstantin V.; Chernogorskiy, Sergey A.; Sorokozherdyev, Kirill G.; Golubev, Vadim A.
Abstract
This paper presents an analysis of the economic development of the region of St.Petersburg with an application of ADL-model. The model is built on the basis of quarterly macroeconomic data for 13 years. The equations were built on such regional indicators as average wages, GRP, as well as the birth rate. The influencing factors of the model represent the share of various types of economic activity in the GRP. Also, on the basis of the model, there were made forecasting of the endogenous variables for 8 quarters ahead, using the extrapolated data for independent variables. In order to perform the task the software package for econometric modeling Gretl was used.