An improved damaging model formulated within the framework of bounding surface for structured clays was proposed. The model was intended to describe the effects of structure degradation due to geotechnical loading. Th...An improved damaging model formulated within the framework of bounding surface for structured clays was proposed. The model was intended to describe the effects of structure degradation due to geotechnical loading. The predictive capability of the model was compared with those of triaxial compression test on Tianjin soft clays. The results show that, by incorporating a new damage function into the model, the reduction of elastic bulk and shear modulus with elastic deformations and the reduction of plastic bulk modulus and shear modulus with plastic deformations are able to be appreciable. Before the axial strain reaches 15%, the axial strain computed from the model is smaller than that from the test under the drained condition. Under the undrained condition, after the axial strain reaches 1%, the axial strain increases quickly because of the complete loss of structure and stiffness; and the result computed from the model is nearly equal to that from the model without the incorporation of the damage function due to less plastic strain under undrained condition test.展开更多
Because of the powerful mapping ability, back propagation neural network (BP-NN) has been employed in computer-aided product design (CAPD) to establish the property prediction model. The backward problem in CAPD is to...Because of the powerful mapping ability, back propagation neural network (BP-NN) has been employed in computer-aided product design (CAPD) to establish the property prediction model. The backward problem in CAPD is to search for the appropriate structure or composition of the product with desired property, which is an optimization problem. In this paper, a global optimization method of using the a BB algorithm to solve the backward problem is presented. In particular, a convex lower bounding function is constructed for the objective function formulated with BP-NN model, and the calculation of the key parameter a is implemented by recurring to the interval Hessian matrix of the objective function. Two case studies involving the design of dopamine β-hydroxylase (DβH) inhibitors and linear low density polyethylene (LLDPE) nano composites are investigated using the proposed method.展开更多
基金Project(07JCZDJC09800) supported by Tianjin Natural Science FoundationProject(50508021) supported by the National Natural Science Foundation of China
文摘An improved damaging model formulated within the framework of bounding surface for structured clays was proposed. The model was intended to describe the effects of structure degradation due to geotechnical loading. The predictive capability of the model was compared with those of triaxial compression test on Tianjin soft clays. The results show that, by incorporating a new damage function into the model, the reduction of elastic bulk and shear modulus with elastic deformations and the reduction of plastic bulk modulus and shear modulus with plastic deformations are able to be appreciable. Before the axial strain reaches 15%, the axial strain computed from the model is smaller than that from the test under the drained condition. Under the undrained condition, after the axial strain reaches 1%, the axial strain increases quickly because of the complete loss of structure and stiffness; and the result computed from the model is nearly equal to that from the model without the incorporation of the damage function due to less plastic strain under undrained condition test.
文摘Because of the powerful mapping ability, back propagation neural network (BP-NN) has been employed in computer-aided product design (CAPD) to establish the property prediction model. The backward problem in CAPD is to search for the appropriate structure or composition of the product with desired property, which is an optimization problem. In this paper, a global optimization method of using the a BB algorithm to solve the backward problem is presented. In particular, a convex lower bounding function is constructed for the objective function formulated with BP-NN model, and the calculation of the key parameter a is implemented by recurring to the interval Hessian matrix of the objective function. Two case studies involving the design of dopamine β-hydroxylase (DβH) inhibitors and linear low density polyethylene (LLDPE) nano composites are investigated using the proposed method.
