Numerical study on the response of steel-laminated elastomeric bearings subjected to variable axial loads and development of local tensile stresses

Kalfas, Konstantinos N.; Mitoulis, Stergios A.; Katakalos, Konstantinos

doi:10.1016/j.engstruct.2016.12.015

Cited by 64 publications

(35 citation statements)

References 28 publications

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“…Secondly, the effect of rotation of the supports have been considered. The non-linear behavior shown in in numerical simulations [7,10] was reproduced with two sensitivity analyses. The results show how a more developed model needs to include both the reduction of G and the effect of the rotation.…”

Section: Resultsmentioning

confidence: 89%

“…Fig. 5 shows the shear force -displacement relationship for variable values of the axial load (2MPa and 14 MPa), as calculated by the theoretical model (red line), in relationship with the ones predicted by the numerical simulation (blue line) [7]. It is possible to see that the displacements increase linearly with the lateral shear force.…”

Section: Case Studymentioning

confidence: 79%

“…In this paper, the multilayer elastomeric bearing has been taken from the ones tested experimentally at University of Surrey and numerically in recent research [7,10] shown in Figure 1 and Table 1, where the geometry of the reference bearing is described in details. The circular steel-laminated elastomeric bearing consists of thirty layers of a hyperelastic material with 4 mm thickness each, alternating with twenty-nine steel shims with thickness of 3.1 mm each.…”

Section: Case Studymentioning

confidence: 99%

“…Figure 2. Response of the reference steel-laminated elastomeric bearing for variable axial loads (shear strain 375%) for one cycle of loading [7] 3 THEORETICAL MODEL…”

Section: Case Studymentioning

confidence: 99%

“…Figure 6 shows the comparison between the numerical simulation outputs (blue line, [7]), the theoretic model [8] (with constant G, in red) and the modified G (with equation 1, in green). It is shown that the theoretical approach and the numerical results improves when equation (1) Figure 6 -Shear force-displacement: comparison between the numerical simulation outputs (blue line, [7]), the theoretic model [8] (constant G) and the modified G (with equation (1)) for axial load: 2 MPa and 14 MPa.…”

Section: G Modulusmentioning

confidence: 99%

See 4 more Smart Citations

Study on the Response of Elastomeric Bearings With 3d Numerical Simulations and Experimental Validation

Forcellini¹,

Mitoulis²,

Kalfas³

2017

Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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Section: Resultsmentioning

confidence: 89%

Section: Case Studymentioning

confidence: 79%

Section: Case Studymentioning

confidence: 99%

“…Figure 2. Response of the reference steel-laminated elastomeric bearing for variable axial loads (shear strain 375%) for one cycle of loading [7] 3 THEORETICAL MODEL…”

Section: Case Studymentioning

confidence: 99%

Section: G Modulusmentioning

confidence: 99%

See 3 more Smart Citations

Study on the Response of Elastomeric Bearings With 3d Numerical Simulations and Experimental Validation

Forcellini¹,

Mitoulis²,

Kalfas³

2017

Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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Coupled structural and heat conduction FE analysis of laminated high damping rubber bearing

Miyamura

Ohsaki

Fujiwara

et al. 2021

Earthq Engng Struct Dyn

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A framework for coupled structural and heat conduction finite element analysis is developed for laminated high damping rubber bearings (HDRBs), and coupled analyses are conducted for full‐scale tests of an HDRB using the shaking table at E‐Defense. An HDRB, which is used in base‐isolated buildings, is modeled using hexahedral solid elements. The high damping rubber is modeled as an overlaid viscohyperelastic and elastic‐plastic constitutive model. However, material parameters are identified using the results for the HDRB subjected to one‐directional loading, and temperature dependences of the parameters are taken into account by a simple method based on empirical formulae for the HDRB because no cyclic coupon test was conducted for the high damping rubber used in the full‐scale tests. The combined structural and heat conduction analyses are conducted for a number of loading cases. The same hexahedral mesh of the HDRB is used for both structural and heat conduction analyses. Analysis results are presented for a one‐directional cyclic loading test, two‐directional loading test with elliptical orbit, and earthquake loading test. The results obtained by the tests and those obtained by the coupled structural and heat conduction analyses are compared. The coupling effect of the mechanical and thermal behaviors is clearly shown in the analysis results, although reductions of the equivalent stiffness and damping are not large because the number of loading cycles in the present analyses is limited.

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A deep learning method to monitor axial pressure and shear deformation of rubber bearings under coupled compression and shear loading

Zeng

Pan

2023

Earthq Engng Struct Dyn

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Laminated rubber bearings are the key components of base isolated structures. It is important to effectively monitor the axial pressure and shear deformation in rubber bearings. In previous studies, the axial pressure and shear deformation of rubber bearings have been monitored separately using wavelet‐packet‐based method. However, when the axial pressure and deformation of rubber bearings change at the same time, the prediction error of the above method is large. Therefore, this paper proposed a new deep neural network architecture, named P&D‐NET to monitor the axial pressure and shear deformation simultaneously. The P&D‐NET combines wavelet packet decomposition method and fully connected neural network. In this study, the coupling effects of axial pressure and shear deformation monitoring are studied by full‐scale experiments. The details of P&D‐NET are also introduced. Three full‐scale smart rubber bearings (SRB) were tested under different axial pressure and shear deformation to form a real measured dataset. The influence of feature extraction methods, network structures, and weighting coefficient in loss function was investigated to optimize the network. By using the optimal hyperparameters, the root‐mean‐square error (RMSE) of axial pressure prediction and shear deformation prediction in the test set is 1.41 MPa and 17.6%, which has reduced the error by up to 68.8% compared to the previous wavelet‐packet‐based method.

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Numerical study on the response of steel-laminated elastomeric bearings subjected to variable axial loads and development of local tensile stresses

Cited by 64 publications

References 28 publications

Study on the Response of Elastomeric Bearings With 3d Numerical Simulations and Experimental Validation

Study on the Response of Elastomeric Bearings With 3d Numerical Simulations and Experimental Validation

Coupled structural and heat conduction FE analysis of laminated high damping rubber bearing

A deep learning method to monitor axial pressure and shear deformation of rubber bearings under coupled compression and shear loading

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