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Article
Publication date: 24 April 2007

F. Daneshmand and S. Niroomandi

This paper seeks to extend the application of the natural neighbour Galerkin method to vibration analysis of fluid‐structure interaction problems.

390

Abstract

Purpose

This paper seeks to extend the application of the natural neighbour Galerkin method to vibration analysis of fluid‐structure interaction problems.

Design/methodology/approach

The natural element method (NEM) which is a meshless technique is used to simulate the vibration analysis of the fluid‐structure interaction systems. The method uses the natural neighbour interpolation for the construction of test and trial functions. Displacement variable is used for both the solid and the fluid domains, whereas the fluid displacement is written as the gradient of a potential function. Two classical examples are considered: free vibration of a flexible cavity filled with liquid and vibration of an open vessel containing liquid. The corresponding eigenvalue problems are solved and the results are compared with the finite element method (FEM) and analytical solutions to show the accuracy and convergence of the method.

Findings

The performance of the NEM is investigated in the computation of the vibration modes of the fluid‐structure interaction problems. Good agreement with analytical and FEM solutions are observed. Through the notable obtained results, it is found that the NEM can also be used in vibration analysis of fluid‐structure interaction problems as it has been successfully applied to some problems in solid and fluid mechanics during the recent years.

Originality/value

In spite of notable achievements in solving some problems in solid and fluid mechanics using NEM, the vibration analysis of fluid‐structure interaction problems, as considered in this paper, has not been investigated so far.

Details

Engineering Computations, vol. 24 no. 3
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 29 May 2009

Narges Dialami and Farhang Daneshmand

The purpose of this paper is to extend the application of natural neighbor Galerkin Method (NNGM) to deflection analysis of inflatable structures such as new and modern textile…

703

Abstract

Purpose

The purpose of this paper is to extend the application of natural neighbor Galerkin Method (NNGM) to deflection analysis of inflatable structures such as new and modern textile structures under arbitrary conditions.

Design/methodology/approach

Inflatable structures have a proper mechanical strength when they are inflated at different pressures. NNGM or natural element method (NEM) is defined as a new meshfree method based on the natural neighbor interpolation to analyze the deflections of these structures under arbitrary pressures, load and support conditions. The whole interpolation is built with regard to the natural neighbor nodes and Voronoi tessellation of the given point.

Findings

The performance of NNGM is investigated in the deflection analysis of inflatable tubes and panels. The excellent agreement between the presented modeling and analytical results and also finite element solutions and experiment are observed.

Originality/value

Despite the wide usage of NNGM in many engineering problems, this comparison shows the other aspect of application of NNGM in the deflection analysis of inflatable structures, not previously examined.

Details

Engineering Computations, vol. 26 no. 4
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 4 May 2020

Liang Ruixin, Joanne Yip, Winnie Yu, Lihua Chen and Newman Lau

The breasts are mainly fatty and connective tissues with no muscles that directly support them, so wearing sports bras is one of the most effective means of alleviating the…

569

Abstract

Purpose

The breasts are mainly fatty and connective tissues with no muscles that directly support them, so wearing sports bras is one of the most effective means of alleviating the discomfort of breast movement and potential injury during vigorous physical exercise. However, the design and development processes of traditional sports bras are time-consuming and costly. Hence, a novel method of simulating the static contact pressure between a sports bra and women’s body based on the finite element (FE) and artificial neural network (ANN) models is developed in this study to contribute to the design considerations of sports bras.

Design/methodology/approach

Three-dimensional FE models of a female subject and sports bras with different fabric properties are developed to determine the amount of contact pressure exerted onto the body. The FE results are then verified by measuring the amount of pressure exerted by the sports bra on the skin with pressure sensors. The Taguchi technique is used to effectively reduce the number of trials from 625 to only 25 cases. These 25 results obtained through FE modelling are then used to provide the training set for the ANNs. Finally, a comparison between the FE and ANN results is carried out.

Findings

A novel model of the static contact pressure between a sports bra and human subject based on the FE and ANN methods is presented in this paper. The root mean square error values show that there is only a small difference between the FE and ANN results.

Originality/value

The ANN function established in this study can be used to predict the mechanical behaviours of breasts and has a fundamental impact on the computer-aided design of functional garments in general.

Details

International Journal of Clothing Science and Technology, vol. 32 no. 6
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 17 October 2024

R. Surya Prakash and N. Parthasarathi

The purpose of this study is to perform a numerical analysis of fiber-reinforced polymer (FRP) retrofitting in reinforced concrete (RC) joints at high temperatures and predict…

58

Abstract

Purpose

The purpose of this study is to perform a numerical analysis of fiber-reinforced polymer (FRP) retrofitting in reinforced concrete (RC) joints at high temperatures and predict models using artificial neural networks (ANN). The aim was to gain insights into their structural behavior across a range of loading conditions from room temperature to 800°C. Additionally, the research assessed the efficiency of carbon fiber-reinforced polymer (CFRP), glass fiber reinforced polymer (GFRP) and aramid fiber reinforced polymer (AFRP) strengthening in enhancing the structural performance of the critical sections.

Design/methodology/approach

The linear numerical simulations were conducted to evaluate the performance of RC beam-column joints using finite element modelling (FEM) analysis. The ANN model demonstrated exceptional effectiveness in predicting the stiffness of frames with openings, establishing itself as the premier machine learning algorithm for frame stiffness estimation. In the conventional model, 300°C was proven to be an effective temperature approach. Subsequently, maintaining a constant temperature of 300°C, an in-depth analysis of nearly 30 models of three retrofitting techniques was conducted under thermomechanical loading.

Findings

The CFRP retrofits yielded 15% less deflection and 30% more stress than the remaining FRPs, and the ANN models predicted the deflection, main stresses, bending moment and shear force. The ANN model results were compared with those of other frequently used models. The R thresholds (R = 0.954, 0.981, 0.986, 0.968, 0.978 and 0.936) for training, testing and validation indicated that the ANN model achieved data variability. The findings indicate that the ANN model is more accurate because of the strong connection between the numerical model and the prediction.

Originality/value

To identify the pinpoint of critical segments within the rehabilitation section and determine the most effective wrapping method among the three laminates.

Details

Journal of Structural Fire Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-2317

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Article
Publication date: 25 July 2024

Shashikant Mahadev Nagargoje and Milinda Ashok Mahajan

The purpose of this paper is to study the shearing performance under bi-directional loading of an interior beam–column joint (BCJ) sub-assemblage using the finite element analysis…

14

Abstract

Purpose

The purpose of this paper is to study the shearing performance under bi-directional loading of an interior beam–column joint (BCJ) sub-assemblage using the finite element analysis (FEA) tool (midas fea), validated in this research.

Design/methodology/approach

The BCJ can be defined as an essential part of the column that transfers the forces at the ends of the members connected to it. The members of the rigid jointed plane frame resist external forces by developing twisting moment, bending moment, axial force and shear force in the frame members. On the type of joints, the response to the action of lateral loads depends on reinforced concrete (RC) framed structures. The joint is considered rigid if the angle between the members remains unchanged during the structural deformation. This work examined the shear deformation, load displacement and strength of a non-seismically detailed internal concentric RC joint using non-linear FEA. The bi-directional loading imposes the oblique compression zone on one joint corner. This joint core’s oblique compression strut mechanism differs significantly from that under unidirectional loading. The numerical results are compared with experimental results in this study, with the data published in the literature.

Findings

Numerical analysis results show that, in the comparative study of numerical and experimental values, the FEA tool predicts the behaviour of the RC BCJ well. The discrepancy between the experimental and numerical results amounts to 6 to 12% end displacement of the beam, 7% resultant joint shear force, 4.23% column bar strain and 0.70% hoop strain.

Originality/value

The current code of practice describes the joint sub-assemblage behaviour along the single axis individually. In the non-orthogonal system, the superposition of the two axes for joint space results in overlapping the stresses and, hence, the formation of the oblique strut. This may result in a reduction in the joint capacity under bi-directional loading. The behaviour must be explored in depth, and an attempt is made for further exploration.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 10 December 2024

Abdellatif Selmi and Ali Raza

The aim of the current study is to recommend and compare the estimates of finite element model (FEM), analytical model, and artificial neural networks (ANN) model for capturing…

8

Abstract

Purpose

The aim of the current study is to recommend and compare the estimates of finite element model (FEM), analytical model, and artificial neural networks (ANN) model for capturing the LCC of FCSC members. A database comprising 325 FCSC columns was constructed from previous studies to propose FEM and ANN models while the analytical model was proposed based on a database of 712 samples and encasing mechanics of steel tube and FRP wraps. The concrete damage plastic model was used for concrete along with bilinear and linear elastic models for steel tube and FRP wraps, respectively. Analytical and ANN models effectively considered the lateral encasing mechanism of FCSC columns for accurate predictions.

Design/methodology/approach

The study aimed to compare the prediction accuracy of finite element (FEM), analytical, and artificial neural network (ANN) models for the load-carrying capacity (LCC) of fiber reinforced polymer (FRP)-encased concrete-filled steel tube (CFST) compression members (FCSC). A database of 325 FCSC columns was developed for FEM and ANN models, while the analytical model was based on 712 samples, utilizing encasing mechanics of steel tube and FRP wraps. FEM used a concrete damage plastic model, bilinear steel tube, and linear elastic FRP models. Statistical accuracy was evaluated using MAE, MAPE, R², RMSE, and a 20-index across all models.

Findings

Based on the experimental database, the FEM presented the accuracies in the form of statistical parameters MAE = 223.76, MAPE = 285.32, R2 = 0.94, RMSE = 210.43 and a20-index = 0.83. The analytical model showed the statistics of MAE = 427.229, MAPE = 283.649, R2 = 0.8149, RMSE = 275.428 and a20-index = 0.73 while ANN models portrayed the predictions with MAE = 195, MAPE = 229.67, R2 = 0.981, RMSE = 174 and a20-index = 0.89 for the LCC of FCSC columns.

Originality/value

Although various investigations have already been performed on the prediction of the load-carrying capacity (LCC) of fiber reinforced polymer (FRP)-encased concrete-filled steel tube (CFST) compression members (FCSC) using small and noisy data, none of them compared the accuracy of prediction of different modeling techniques based on a refined large database.

Details

Multidiscipline Modeling in Materials and Structures, vol. 21 no. 2
Type: Research Article
ISSN: 1573-6105

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