A dynamic nondestructive damage detection methodology for orthotropic plate structures

Gandomi, Amir Hossein,Sahab, Mohammad G.,Rahai, Alireza Techno-Press 2011 Structural Engineering and Mechanics, An Int'l Jou Vol.39 No.2

This paper presents a methodology to detect and locate damages and faults in orthotropic plate structures. A specific damage index based on dynamic mode shapes of the damaged and undamaged structures has been introduced. The governing differential equation on transverse deformation, the transverse shear force equations and the invariant expression for the sum of transverse loading of an orthotropic plate are employed to obtain the aforementioned damage indices. The validity of the proposed methodology for isotropic and orthotropic damage states is demonstrated using a numerical example. It is shown that the algorithm is able to detect damages for both isotropic and orthotropic damage states acceptably.

Nonlinear modeling of shear strength of SFRC beams using linear genetic programming

Gandomi, A.H.,Alavi, A.H.,Yun, G.J. Techno-Press 2011 Structural Engineering and Mechanics, An Int'l Jou Vol.38 No.1

A new nonlinear model was developed to evaluate the shear resistance of steel fiber-reinforced concrete beams (SFRCB) using linear genetic programming (LGP). The proposed model relates the shear strength to the geometrical and mechanical properties of SFRCB. The best model was selected after developing and controlling several models with different combinations of the influencing parameters. The models were developed using a comprehensive database containing 213 test results of SFRC beams without stirrups obtained through an extensive literature review. The database includes experimental results for normal and high-strength concrete beams. To verify the applicability of the proposed model, it was employed to estimate the shear strength of a part of test results that were not included in the modeling process. The external validation of the model was further verified using several statistical criteria recommended by researchers. The contributions of the parameters affecting the shear strength were evaluated through a sensitivity analysis. The results indicate that the LGP model gives precise estimates of the shear strength of SFRCB. The prediction performance of the model is significantly better than several solutions found in the literature. The LGP-based design equation is remarkably straightforward and useful for pre-design applications.

A dynamic nondestructive damage detection methodology for orthotropic plate structures

Amir Hossein Gandomi,Mohammad G. Sahab,Alireza Rahai 국제구조공학회 2011 Structural Engineering and Mechanics, An Int'l Jou Vol.39 No.2

This paper presents a methodology to detect and locate damages and faults in orthotropic plate structures. A specific damage index based on dynamic mode shapes of the damaged and undamaged structures has been introduced. The governing differential equation on transverse deformation, the transverse shear force equations and the invariant expression for the sum of transverse loading of an orthotropic plate are employed to obtain the aforementioned damage indices. The validity of the proposed methodology for isotropic and orthotropic damage states is demonstrated using a numerical example. It is shown that the algorithm is able to detect damages for both isotropic and orthotropic damage states acceptably.

Formulation of elastic modulus of concrete using linear genetic programming

Amir Hossein Gandomi,Amir Hossein Alavi,Mohammad Ghasem Sahab,Parvin Arjmandi 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.6

This paper proposes a novel approach for the formulation of elastic modulus of both normal-strength concrete (NSC) and high-strength concrete (HSC) using a variant of genetic programming (GP), namely linear genetic programming (LGP). LGP-based models relate the modulus of elasticity of NSC and HSC to the compressive strength, as similarly presented in several codes of practice. The models are developed based on experimental results collected from the literature. A subsequent parametric analysis is further carried out to evaluate the sensitivity of the elastic modulus to the compressive strength variations. The results demonstrate that the proposed formulas can predict the elastic modulus with an acceptable degree of accuracy. The LGP results are found to be more accurate than those obtained using the buildings codes and various solutions reported in the literature. The LGP-based formulas are quite simple and straightforward and can be used reliably for routine design practice.

Formulation of Uplift Capacity of Suction Caissons Using Multi Expression Programming

Amir Hossein Gandomi,Amir Hossein Alavi,Gun Jin Yun 대한토목학회 2011 KSCE JOURNAL OF CIVIL ENGINEERING Vol.15 No.2

Suction caissons have increasingly been used as foundations and anchors for deepwater offshore structures in the last decade. The increased use of suction caissons defines a serious need to develop more authentic methods for simulating their behavior. Reliable assessment of uplift capacity of caissons in cohesive soils is a critical issue facing design engineers. This paper proposes a new approach for the formulation of the uplift capacity of suction caissons using a promising variant of Genetic Programming (GP),namely Multi Expression Programming (MEP). The proposed model is developed based on experimental results obtained from the literature. The derived MEP-based formula takes into account the effect of aspect ratio of caisson, shear strength of clayey soil, point of application and angle of inclination of loading, soil permeability and loading rate. A subsequent parametric analysis is carried out and the trends of the results are confirmed via previous studies. The results indicate that the MEP formulation can predict the uplift capacity of suction caissons with an acceptable level of accuracy. The proposed formula provides a prediction performance better than or comparable with the models found in the literature. The MEP-based simplified formulation is particularly valuable for providing an analysis tool accessible to practicing engineers.

Nonlinear modeling of shear strength of SFRC beams using linear genetic programming

A.H. Gandomi,A.H. Alavi,G.J. Yun 국제구조공학회 2011 Structural Engineering and Mechanics, An Int'l Jou Vol.38 No.1

A new nonlinear model was developed to evaluate the shear resistance of steel fiberreinforced concrete beams (SFRCB) using linear genetic programming (LGP). The proposed model relates the shear strength to the geometrical and mechanical properties of SFRCB. The best model was selected after developing and controlling several models with different combinations of the influencing parameters. The models were developed using a comprehensive database containing 213 test results of SFRC beams without stirrups obtained through an extensive literature review. The database includes experimental results for normal and high-strength concrete beams. To verify the applicability of the proposed model, it was employed to estimate the shear strength of a part of test results that were not included in the modeling process. The external validation of the model was further verified using several statistical criteria recommended by researchers. The contributions of the parameters affecting the shear strength were evaluated through a sensitivity analysis. The results indicate that the LGP model gives precise estimates of the shear strength of SFRCB. The prediction performance of the model is significantly better than several solutions found in the literature. The LGP-based design equation is remarkably straightforward and useful for pre-design applications.

A data mining approach to compressive strength of CFRP-confined concrete cylinders

Mousavi, S.M.,Alavi, A.H.,Gandomi, A.H.,Esmaeili, M. Arab,Gandomi, M. Techno-Press 2010 Structural Engineering and Mechanics, An Int'l Jou Vol.36 No.6

In this paper, compressive strength of carbon fiber reinforced polymer (CFRP) confined concrete cylinders is formulated using a hybrid method coupling genetic programming (GP) and simulated annealing (SA), called GP/SA, and a robust variant of GP, namely multi expression programming (MEP). Straightforward GP/SA and MEP-based prediction equations are derived for the compressive strength of CFRP-wrapped concrete cylinders. The models are constructed using two sets of predictor variables. The first set comprises diameter of concrete cylinder, unconfined concrete strength, tensile strength of CFRP laminate, and total thickness of CFRP layer. The most widely used parameters of unconfined concrete strength and ultimate confinement pressure are included in the second set. The models are developed based on the experimental results obtained from the literature. To verify the applicability of the proposed models, they are employed to estimate the compressive strength of parts of test results that were not included in the modeling process. A sensitivity analysis is carried out to determine the contributions of the parameters affecting the compressive strength. For more verification, a parametric study is carried out and the trends of the results are confirmed via some previous studies. The GP/SA and MEP models are able to predict the ultimate compressive strength with an acceptable level of accuracy. The proposed models perform superior than several CFRP confinement models found in the literature. The derived models are particularly valuable for pre-design purposes.

A data mining approach to compressive strength of CFRP-confined concrete cylinders

S.M. Mousavi,A.H. Alavi,A.H. Gandomi,M. Arab Esmaeili,M. Gandomi 국제구조공학회 2010 Structural Engineering and Mechanics, An Int'l Jou Vol.36 No.6

In this paper, compressive strength of carbon fiber reinforced polymer (CFRP) confined concrete cylinders is formulated using a hybrid method coupling genetic programming (GP) and simulated annealing (SA), called GP/SA, and a robust variant of GP, namely multi expression programming (MEP). Straightforward GP/SA and MEP-based prediction equations are derived for the compressive strength of CFRP-wrapped concrete cylinders. The models are constructed using two sets of predictor variables. The first set comprises diameter of concrete cylinder, unconfined concrete strength, tensile strength of CFRP laminate, and total thickness of CFRP layer. The most widely used parameters of unconfined concrete strength and ultimate confinement pressure are included in the second set. The models are developed based on the experimental results obtained from the literature. To verify the applicability of the proposed models, they are employed to estimate the compressive strength of parts of test results that were not included in the modeling process. A sensitivity analysis is carried out to determine the contributions of the parameters affecting the compressive strength. For more verification, a parametric study is carried out and the trends of the results are confirmed via some previous studies. The GP/SA and MEP models are able to predict the ultimate compressive strength with an acceptable level of accuracy. The proposed models perform superior than several CFRP confinement models found in the literature. The derived models are particularly valuable for pre-design purposes.

New Synthesis of Perhydrotriazolotriazoles Catalyzed by TiCl₄ under Ambient Conditions

Safari, J.,Gandomi-Ravandi, S.,Ghotbinejad, M. Korean Chemical Society 2012 대한화학회지 Vol.56 No.1

Aromatic 2,3-diazabuta-1,3-dienes in glacial acetic acid with isothiocyanate in the presence of catalyst $TiCl_4$ at room temperature produced via criss-cross cycloaddition reactions the corresponding perhydro[1,2,4]triazolo[1,2-a][1,2,4] triazole-1,5-dithiones in relatively high yields and short reaction time.

Modeling of compressive strength of HPC mixes using a combined algorithm of genetic programming and orthogonal least squares

Mousavi, S.M.,Gandomi, A.H.,Alavi, A.H.,Vesalimahmood, M. Techno-Press 2010 Structural Engineering and Mechanics, An Int'l Jou Vol.36 No.2

In this study, a hybrid search algorithm combining genetic programming with orthogonal least squares (GP/OLS) is utilized to generate prediction models for compressive strength of high performance concrete (HPC) mixes. The GP/OLS models are developed based on a comprehensive database containing 1133 experimental test results obtained from previously published papers. A multiple least squares regression (LSR) analysis is performed to benchmark the GP/OLS models. A subsequent parametric study is carried out to verify the validity of the models. The results indicate that the proposed models are effectively capable of evaluating the compressive strength of HPC mixes. The derived formulas are very simple, straightforward and provide an analysis tool accessible to practicing engineers.