Computational Machine Learning Representation for the Flexoelectricity Effect in Truncated Pyramid Structures

In this study,machine learning representation is introduced to evaluate the flexoelectricity effect in truncated pyramid nanostructure under compression.A Non-Uniform Rational B-spline(NURBS)based IGA formulation is employed to model the flexoelectricity.We investigate 2D system with an isotropic linear elastic material under plane strain conditions discretized by 45×30 grid of B-spline elements.Six input parameters are selected to construct a deep neural network(DNN)model.They are the Young's modulus,two dielectric permittivity constants,the longitudinal and transversal flexoelectric coefficients and the order of the shape function.The outputs of interest are the strain in the stress direction and the electric potential due flexoelectricity.The dataset are generated from the forward analysis of the flexoelectric model.80%of the dataset is used for training purpose while the remaining is used for validation by checking the mean squared error.In addition to the input and output layers,the developed DNN model is composed of four hidden layers.The results showed high predictions capabilities of the proposed method with much lower computational time in comparison to the numerical model.

Structural damage assessment criteria for reinforced concrete buildings by using a Fuzzy Analytic Hierarchy process

Reinforced concrete structures are often exposed to many types of damages and deteriorations due to different causes and exposure conditions during their life cycle.Assessment of such structures is inherently subjected to uncertainty and ambiguity,where subjective opinion and incomplete numeric data are unavoidable.In the damage assessment process,estimating the importance of assessment criteria is an important field in itself,and depends heavily on the experience and expertise of experts.The aim of this study is to present a fuzzy-based assessment model,which estimates the importance of structural assessment criteria for concrete buildings.The work aims also at studying,identifying,and prioritizing assessment criteria.These assessment criteria are based on close visual inspections and simple measurements that do not require special testing or long-term investigation.The main assessment criteria include the state of building history,environmental conditions,structural capacity,durability,and professional involvement in construction.Each of them has two levels of sub-criteria.The criteria weights are obtained based on the opinions of experts using the Fuzzy Analytic Hierarchy Process(FAHP)method.The application of the FAHP method showed that the most important criteria is the structural capacity with a weighting factor of 50.1%,followed by the environmental condition as second,with a weighting factor of 22.5%.