Rapid prediction of inelastic bending moments in RC beams considering cracking

K. A. Patel,Sandeep Chaudhary,A.K. Nagpal 사단법인 한국계산역학회 2016 Computers and Concrete, An International Journal Vol.18 No.6

A methodology using neural networks has been proposed for rapid prediction of inelastic bending moments in reinforced concrete continuous beams subjected to service load. The closed form expressions obtained from the trained neural networks take into account cracking in concrete at in-span and at near the internal supports and tension stiffening effect. The expressions predict the inelastic moments (considering the concrete cracking) from the elastic moments (neglecting the concrete cracking) at supports. Three separate neural networks are trained since these have been postulated to represent all the beams having any number of spans. The training, validating, and testing data sets for the neural networks are generated using an analytical-numerical procedure of analysis. The proposed expressions are verified for example beams of different number of spans and cross-section properties and the errors are found to be small. The proposed expressions, at minimal input data and computation effort, yield results that are close to FEM results. The expressions can be used in preliminary every day design as they enable a rapid prediction of inelastic moments and require a computational effort that is a fraction of that required for the available methods in literature.

A tension stiffening model for analysis of RC flexural members under service load

K. A. Patel,Sandeep Chaudhary,A.K. Nagpal 사단법인 한국계산역학회 2016 Computers and Concrete, An International Journal Vol.17 No.1

Tension-stiffening is the contribution of concrete between the cracks to carry tensile stresses after cracking in Reinforced Concrete (RC) members. In this paper, a tension-stiffening model has been proposed for computationally efficient nonlinear analysis of RC flexural members subjected to service load. The proposed model has been embedded in a typical cracked span length beam element. The element is visualized to consist of at the most five zones (cracked or uncracked). Closed form expressions for flexibility and stiffness coefficients and end displacements have been obtained for the cracked span length beam element. Further, for use in everyday design, a hybrid analytical-numerical procedure has been developed for nonlinear analysis of RC flexural members using the proposed tension-stiffening model. The procedure yields deflections as well as redistributed bending moments. The proposed model (and developed procedure) has been validated by the comparison with experimental results reported elsewhere and also by comparison with the Finite Element Method (FEM) results. The procedure would lead to drastic reduction in computational time in case of large RC structures.

Neural network based approach for rapid prediction of deflections in RC beams considering cracking

K. A. Patel,Sandeep Chaudhary,A.K. Nagpal 사단법인 한국계산역학회 2017 Computers and Concrete, An International Journal Vol.19 No.3

Maximum deflection in a beam is a serviceability design criterion and occurs generally at or close to the mid-span. This paper presents a methodology using neural networks for rapid prediction of mid-span deflections in reinforced concrete beams subjected to service load. The closed form expressions are further obtained from the trained neural networks. The closed form expressions take into account cracking in concrete at in-span and at near the interior supports and tension stiffening effect. The expressions predict the inelastic deflections (incorporating the concrete cracking) from the elastic moments and the elastic deflections (neglecting the concrete cracking). Five separate neural networks are trained since these have been postulated to represent all beams having any number of spans. The training, validating, and testing data sets for the neural networks are generated using an analytical-numerical procedure of analysis. The proposed expressions have been verified by comparison with the experimental results reported elsewhere and also by comparison with the finite element method (FEM). The proposed expressions, at minimal input data and minimal computation effort, yield results that are close to FEM results. The expressions can be used in every day design since the errors are found to be small.

An analytical-numerical procedure for cracking and time-dependent effects in continuous composite beams under service load

A.K. Nagpal,Sandeep Chaudhary,Umesh Pendharkar 국제구조공학회 2007 Steel and Composite Structures, An International J Vol.7 No.3

An analytical-numerical procedure has been presented in this paper to take into account the nonlinear effects of concrete cracking and time-dependent effects of creep and shrinkage in the concrete portion of the continuous composite beams under service load. The procedure is analytical at the element level and numerical at the structural level. The cracked span length beam element consisting of uncracked zone in middle and cracked zones near the ends has been proposed to reduce the computational effort. The progressive nature of cracking of concrete has been taken into account by division of the time into a number of time intervals. Closed form expressions for stiffness matrix, load vector, crack lengths and mid-span deflection of the beam element have been presented in order to reduce the computational effort and bookkeeping. The procedure has been validated by comparison with the experimental and analytical results reported elsewhere and with FEM. The procedure can be readily extended for the analysis of composite building frames where saving in computational effort would be very considerable.

An efficient and novel strategy for control of cracking, creep and shrinkage effects in steel-concrete composite beams

L. K. Varshney,K.A. Patel,Sandeep Chaudhary,A.K. Nagpal 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.70 No.6

Steel-concrete composition is widely used in the construction due to efficient utilization of materials. The service load behavior of composite structures is significantly affected by cracking, creep and shrinkage effects in concrete. In order to control these effects in concrete slab, an efficient and novel strategy has been proposed by use of fiber reinforced concrete near interior supports of a continuous beam. Numerical study is carried out for the control of cracking, creep and shrinkage effects in composite beams subjected to service load. A five span continuous composite beam has been analyzed for different lengths of fiber reinforced concrete near the interior supports. For this purpose, the hybrid analytical-numerical procedure, developed by the authors, for service load analysis of composite structures has been further improved and generalized to make it applicable for composite beams having spans with different material properties along the length. It is shown that by providing fiber reinforced concrete even in small length near the supports; there can be a significant reduction in cracking as well as in deflections. It is also observed that the benefits achieved by providing fiber reinforced concrete over entire span are not significantly more as compared to the use of fiber reinforced concrete in certain length of beam near the interior supports in continuous composite beams.

Rapid Prediction of Deflections in Multi-span Continuous Composite Bridges using Neural Networks

R. K. Gupta,Sushil Kumar,K. A. Patel,Sandeep Chaudhary,A.K. Nagpal 한국강구조학회 2015 International Journal of Steel Structures Vol.15 No.4

This paper proposes closed form expressions for the rapid prediction of deflections in steel-concrete composite bridges of large number of spans subjected to service load. The proposed expressions take into account shear lag effect, flexibility of shear connectors and cracking in concrete slabs. Three separate neural networks have been developed for right exterior span, left exterior span and interior spans. The closed form expressions have been obtained from the neural networks developed in the study. The training, validating and testing data sets for the neural networks are generated using finite element software ABAQUS. The proposed expressions have been validated for number of bridges and the errors are found to be small for practical purposes. Sensitivity studies have been carried out using the proposed expressions to evaluate the suitability of input parameters. The use of the proposed expressions requires a computational effort that is fraction of that required for the finite element analysis, therefore, can be used for rapid prediction of deflection for everyday design.

Rapid prediction of long-term deflections in composite frames

Umesh Pendharkar,Sandeep Chaudhary,K. A. Patel,A.K. Nagpal 국제구조공학회 2015 Steel and Composite Structures, An International J Vol.18 No.3

Deflection in a beam of a composite frame is a serviceability design criterion. This paper presents a methodology for rapid prediction of long-term mid-span deflections of beams in composite frames subjected to service load. Neural networks have been developed to predict the inelastic mid-span deflections in beams of frames (typically for 20 years, considering cracking, and time effects, i.e., creep and shrinkage in concrete) from the elastic moments and elastic mid-span deflections (neglecting cracking, and time effects). These models can be used for frames with any number of bays and stories. The training, validating, and testing data sets for the neural networks are generated using a hybrid analytical-numerical procedure of analysis. Multilayered feed-forward networks have been developed using sigmoid function as an activation function and the back propagation-learning algorithm for training. The proposed neural networks are validated for an example frame of different number of spans and stories and the errors are shown to be small. Sensitivity studies are carried out using the developed neural networks. These studies show the influence of variations of input parameters on the output parameter. The neural networks can be used in every day design as they enable rapid prediction of inelastic mid-span deflections with reasonable accuracy for practical purposes and require computational effort which is a fraction of that required for the available methods.

Effect of creep and shrinkage in a class of composite frame - shear wall systems

Savita Maru,A.K. Nagpal,R.K. Sharma 국제구조공학회 2003 Steel and Composite Structures, An International J Vol.3 No.5

The behaviour of composite frame - shear wall systems with regard to creep and shrinkage with high beam stiffness has been largely unattended until recently since no procedure has been available. Recently an accurate procedure, termed the Consistent Procedure (CP), has been developed which is applicable for low as well as for high beam stiffness. In this paper, CP is adapted for a class of composite frame - shear wall systems comprising of steel columns and R.C. shear walls. Studies are reported for the composite systems with high as well as low beam stiffness. It is shown that considerable load redistribution occurs between the R.C. shear wall and the steel columns and additional moments occur in beams. The magnitude of the load redistribution and the additional moment in the beams depend on the stiffness of the beams. It is also shown that the effect of creep and shrinkage are greater for the composite frame - shear wall system than for the equivalent R.C. frame - shear wall system.

Closed-form Expressions for Long-term Deflections in High-rise Composite Frames

Umesh Pendharkar,K. A. Patel,Sandeep Chaudhary,A.K. Nagpal 한국강구조학회 2017 International Journal of Steel Structures Vol.17 No.1

This paper presents closed-form expressions for rapid prediction of long-term deflections in high-rise steel concrete composite frames subjected to service load. The closed-form expressions predict the inelastic mid-span deflections in beams of frames (typically for 20 years, considering cracking, and time effects, i.e., creep and shrinkage in concrete) from the elastic moments and elastic mid-span deflections (neglecting cracking, and time effects). The expressions also take into account the sagging moments developed in beams due to the substantial differential shortening of adjacent columns in high-rise frames. The expressions can be used for frames with any number of bays and storeys. The expressions have been obtained from trained neural networks. The training, validating, and testing data sets for the neural networks are generated using a hybrid analyticalnumerical procedure of analysis. The proposed expressions are verified for example frames of different number of spans and storeys and the errors are shown to be small. The expressions can be used in every day design as they enable a rapid prediction of inelastic deflections with reasonable accuracy for practical purposes without detailed complex analysis and require computational effort that is a fraction of that required for the available methods.

Rapid Prediction of Long-term Deflections in Steel-Concrete Composite Bridges Through a Neural Network Model

Sushil Kumar,K. A. Patel,Sandeep Chaudhary,A.K. Nagpal 한국강구조학회 2021 International Journal of Steel Structures Vol.21 No.2

This paper proposes a closed-form expression for the rapid prediction of long-term defl ections in simply supported steel– concrete composite bridges under the service load. The proposed expression incorporates the fl exibility of shear connectors, shear lag eff ect and time eff ects (creep and shrinkage) in concrete. The expression has been derived from the trained artifi cial neural network (ANN). The training, validation and testing data sets for the ANN were produced using the validated fi nite element (FE) model. The proposed expression has been verifi ed for a number of specimen-bridges and the errors were observed to be within acceptable limits for practical design purposes. Furthermore, a sensitivity analysis has been performed using the proposed closed-form expression to study the eff ect of the input parameters on the output. The proposed expression requires nominal computational eff ort, compared to the FE analysis and, therefore, can be applied to rapid prediction of defl ections for everyday preliminary design.