scholarly journals Stochastic Model Updating of Bolt-Jointed Structure for Structural Dynamics Applications

2021 ◽  
Vol 18 (2) ◽  
Author(s):  
M.A.S. Aziz Syah ◽  
M. A. Yunus ◽  
M.N. Abdul Rani ◽  
R. Omar ◽  
Akhil Mora
Keyword(s):  
Stochastic Model ◽  
Dynamic Behaviour ◽  
Model Updating ◽  
Stochastic Modelling ◽  
Latin Hypercube Sampling ◽  
Bolted Joints ◽  
Statistical Characteristics ◽  
Experimental Result ◽  
Predicted Model ◽  
Rigid Element

Structural stiffness exerts from joint connections and contact interfaces are significantly affect the dynamic behaviour of the bolt-jointed structure. Randomness in the joint connections due to the manufacturing variability in the identical bolted joints and uncertainty in contact interfaces due to the assambled and reassambled of the joint structure make sets of the dynamic behaviour of the bolt-jointed structure always inconsistent. On this account, a stochastic analytical model needs to be developed for the bolt-jointed structure to be used for uncertain parameters quantification. Hence, this paper is intended to propose an accurate and efficient stochastic analytical modelling of bolt-jointed structure in predicting the dynamic behaviour of the structure due to the randomness in the joint connections and uncertainty in contact interfaces. The aim of the study was accomplished by investigating four different finite element (FE) models of bolt-jointed structure with different element connectors to represent the bolted joints connections, namely rigid element (RBE), beam element (CBEAM), and 2 types of spring elements namely CELAS and CBUSH. Stochastic modelling was conducted by coupled the appropriate FE models with Latin Hypercube Sampling (LHS) algorithm to provide variability sampling due to the randomness in the bolted joints. The experimental modal analysis was performed by reassembled and disassembled the bolted joints to extract the variability in the dynamic behaviour, and the results were compared with LHS using statistical characteristics. Stochastic model updating then was used to minimise the discrepancies between experimental result and predicted model. The result has shown that the CBUSH is the most appropriate connector to accurately predict the dynamic behaviour of the bolt-jointed structure under variability conditions using the stochastic model updating method.

Representation of bolted joints in a structure using finite element modelling and model updating

2020 ◽  
Vol 14 (3) ◽  
pp. 7141-7151 ◽  
Author(s):  
R. Omar ◽  
M. N. Abdul Rani ◽  
M. A. Yunus
Keyword(s):  
Finite Element ◽  
Dynamic Behaviour ◽  
Model Updating ◽  
Complex Structure ◽  
Bolted Joints ◽  
Model Parameters ◽  
Fe Model ◽  
Bolted Joint ◽  
Fe Modelling ◽  
Joint Structure

Efficient and accurate finite element (FE) modelling of bolted joints is essential for increasing confidence in the investigation of structural vibrations. However, modelling of bolted joints for the investigation is often found to be very challenging. This paper proposes an appropriate FE representation of bolted joints for the prediction of the dynamic behaviour of a bolted joint structure. Two different FE models of the bolted joint structure with two different FE element connectors, which are CBEAM and CBUSH, representing the bolted joints are developed. Modal updating is used to correlate the two FE models with the experimental model. The dynamic behaviour of the two FE models is compared with experimental modal analysis to evaluate and determine the most appropriate FE model of the bolted joint structure. The comparison reveals that the CBUSH element connectors based FE model has a greater capability in representing the bolted joints with 86 percent accuracy and greater efficiency in updating the model parameters. The proposed modelling technique will be useful in the modelling of a complex structure with a large number of bolted joints.

scholarly journals The improvement of bolted joints model via finite element model updating method

2021 ◽  
Vol 15 (4) ◽  
pp. 8635-8643
Author(s):  
M. A. Yunus ◽  
M.N. Abdul Rani ◽  
M.A.S. Aziz Shah ◽  
M.S.M. Sani ◽  
Z. Yahya
Keyword(s):  
Mathematical Model ◽  
Sheet Metal ◽  
Dynamic Behaviour ◽  
Model Updating ◽  
Thin Sheet ◽  
Local Deformation ◽  
Bolted Joints ◽  
Fe Model ◽  
Thin Sheet Metal ◽  
Fe Model Updating

Efficient schemes to represent mathematical model of thin-sheet metal structures jointed by bolted joints for accurately predict the structure dynamic behaviour has been a significant unresolved issue in structural dynamics community. The biggest challenge is to efficiently incorporate the joints local deformation effects on the developed mathematical model via finite element (FE) method. Generally, the joints local deformation typically exerts on the joints mating area. To solve this issue, this paper proposes efficient schemes to represent mathematical model of thin-sheet metal structures jointed by bolted joints with application to accurately calculate the structure dynamic behaviour using FE model updating method. The initial FE model of the assembled structure was developed by employed Fastener Connector (CFAST) in MSC NASTRAN software to represent the bolted joints while, the inclusion of the local deformation effects at the bolted joints mating area was represented by contact elements. Then, the responses obtained from the FE model was evaluated by weight up with experimental data. FE model updating (FEMU) method then was utilised for minimising prediction discrepancies originated from the initial FE model based on the experimental data. The proposed scheme shows the accuracy of the initial prediction was improved from 25.03 % to 14.65 %  while the accuracy of the predicted mode shapes via modal assurance criterion (MAC) analysis were above 0.8. Therefore, the findings offer useful schemes for improving the quality of predicted dynamic behaviour, particularly in the thin-sheet metal jointed structure and the developed model can be used with confident for any subsequence dynamic analyses.

scholarly journals A New Stochastic Model Updating Method Based on Improved Cross-Model Cross-Mode Technique

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3290
Author(s):  
Hui Chen ◽  
Bin Huang ◽  
Kong Fah Tee ◽  
Bo Lu
Keyword(s):  
Stochastic Model ◽  
Galerkin Method ◽  
Measurement Errors ◽  
Model Updating ◽  
Measurement Data ◽  
New Method ◽  
Statistical Characteristics ◽  
Practical Significance ◽  
Cross Model ◽  
Coefficient Vector

This paper proposes a new stochastic model updating method to update structural models based on the improved cross-model cross-mode (ICMCM) technique. This new method combines the stochastic hybrid perturbation-Galerkin method with the ICMCM method to solve the model updating problems with limited measurement data and uncertain measurement errors. First, using the ICMCM technique, a new stochastic model updating equation with an updated coefficient vector is established by considering the uncertain measured modal data. Then, the stochastic model updating equation is solved by the stochastic hybrid perturbation-Galerkin method so as to obtain the random updated coefficient vector. Following that, the statistical characteristics of the updated coefficients can be determined. Numerical results of a continuous beam show that the proposed method can effectively cope with relatively large uncertainty in measured data, and the computational efficiency of this new method is several orders of magnitude higher than that of the Monte Carlo simulation method. When considering the rank deficiency, the proposed stochastic ICMCM method can achieve more accurate updating results compared with the cross-model cross-mode (CMCM) method. An experimental example shows that the new method can effectively update the structural stiffness and mass, and the statistics of the frequencies of the updated model are consistent with the measured results, which ensures that the updated coefficients are of practical significance.

Incorporating concepts from physical theory into stochastic modelling of urban runoff pollution

1998 ◽  
Vol 37 (1) ◽  
pp. 179-185
Author(s):  
Morten Grum
Keyword(s):  
Stochastic Model ◽  
Continuous Time ◽  
Measurement Errors ◽  
Physical Theory ◽  
Oxygen Demand ◽  
Stochastic Modelling ◽  
Urban Runoff ◽  
Primary Input ◽  
Deterministic Modelling ◽  
Runoff Pollution

On evaluating the present or future state of integrated urban water systems, sewer drainage models, with rainfall as primary input, are often used to calculate the expected return periods of given detrimental acute pollution events and the uncertainty thereof. The model studied in the present paper incorporates notions of physical theory in a stochastic model of water level and particulate chemical oxygen demand (COD) at the overflow point of a Dutch combined sewer system. A stochastic model based on physical mechanisms has been formulated in continuous time. The extended Kalman filter has been used in conjunction with a maximum likelihood criteria and a non-linear state space formulation to decompose the error term into system noise terms and measurement errors. The bias generally obtained in deterministic modelling, by invariably and often inappropriately assuming all error to result from measurement inaccuracies, is thus avoided. Continuous time stochastic modelling incorporating physical, chemical and biological theory presents a possible modelling alternative. These preliminary results suggest that further work is needed in order to fully appreciate the method's potential and limitations in the field of urban runoff pollution modelling.

Stochastic Modelling of Particle Segregation in a Horizontal Drum Mixer

1992 ◽  
Vol 57 (10) ◽  
pp. 2100-2112 ◽  
Author(s):  
Vladimír Kudrna ◽  
Pavel Hasal ◽  
Andrzej Rochowiecki
Keyword(s):  
Differential Equation ◽  
Diffusion Coefficient ◽  
Stochastic Model ◽  
Diffusion Process ◽  
Stochastic Modelling ◽  
Solid Particles ◽  
Kolmogorov Equation ◽  
Particle Segregation ◽  
Drum Mixer ◽  
Horizontal Drum

A process of segregation of two distinct fractions of solid particles in a rotating horizontal drum mixer was described by stochastic model assuming the segregation to be a diffusion process with varying diffusion coefficient. The model is based on description of motion of particles inside the mixer by means of a stochastic differential equation. Results of stochastic modelling were compared to the solution of the corresponding Kolmogorov equation and to results of earlier carried out experiments.

An applied mathematics perspective on stochastic modelling for climate

2008 ◽  
Vol 366 (1875) ◽  
pp. 2427-2453 ◽  
Author(s):  
Andrew J Majda ◽  
Christian Franzke ◽  
Boualem Khouider
Keyword(s):  
Stochastic Model ◽  
General Circulation ◽  
Applied Mathematics ◽  
Low Frequency ◽  
Lattice Models ◽  
Stochastic Modelling ◽  
General Circulation Models ◽  
Teleconnection Patterns ◽  
Slowing Down ◽  
Low Dimensional

Systematic strategies from applied mathematics for stochastic modelling in climate are reviewed here. One of the topics discussed is the stochastic modelling of mid-latitude low-frequency variability through a few teleconnection patterns, including the central role and physical mechanisms responsible for multiplicative noise. A new low-dimensional stochastic model is developed here, which mimics key features of atmospheric general circulation models, to test the fidelity of stochastic mode reduction procedures. The second topic discussed here is the systematic design of stochastic lattice models to capture irregular and highly intermittent features that are not resolved by a deterministic parametrization. A recent applied mathematics design principle for stochastic column modelling with intermittency is illustrated in an idealized setting for deep tropical convection; the practical effect of this stochastic model in both slowing down convectively coupled waves and increasing their fluctuations is presented here.

STOCHASTIC MODEL OF INFLOW TO RESERVOIR FOR MEDIUM-TERM HYDROLOGICAL FORECASTS WHEN FLOW REGULATING

2021 ◽  
pp. 124-131
Author(s):  
I. G. VELIEV ◽  
◽  
V. V. ILJINICH
Keyword(s):  
Water Management ◽  
Markov Chain ◽  
Stochastic Model ◽  
Decision Makers ◽  
Statistical Characteristics ◽  
Medium Term ◽  
Forecasting Methods ◽  
Balance Accuracy ◽  
Operational Management ◽  
Runoff Model

The article presents a stochastic model of runoff with a five-day discreteness within the water management years. The analysis performed regarding the main statistical characteristics of the inflow to the Krasnodar reservoir has allowed the conclusion that this model, based on a simple Markov chain, satisfies the balance accuracy of hydrological calculations for operational regulation of the runoff. The performed verification calculations have shown that the proposed method for obtaining medium-term runoff forecasts for 5 days, based on the developed stochastic runoff model, is satisfactory to the criteria of efficiency and accuracy of hydrological forecasting methods used in Russia. The specific example has shown that a stochastic runoff model can be useful to decision-makers regarding the operational management of a reservoir in real time.

Numerical Modelling and Bearing Capacity of Reinforced Concrete Beams

2013 ◽  
Vol 577-578 ◽  
pp. 281-284 ◽  
Author(s):  
Oldrich Sucharda ◽  
Jiri Brozovsky ◽  
David Mikolášek
Keyword(s):  
Reinforced Concrete ◽  
Numerical Modelling ◽  
Bearing Capacity ◽  
Concrete Beams ◽  
Plastic Material ◽  
Stochastic Modelling ◽  
Latin Hypercube Sampling ◽  
Reinforced Concrete Beams ◽  
Material Models ◽  
Plastic Model

This paper discusses the fracture-plastic material models for reinforced concrete and use of this model for modelling of reinforced concrete beams. Load-displacement relations and bearing capacity of reinforced concrete beams will be evaluated. A series of original (own) experiments - the beam and data from completed experiments - have been chosen for the numerical modelling. In case of the original experiments - reinforced concrete beams, stochastic modelling based on LHS (Latin Hypercube Sampling) will be carried out in order to estimate the total bearing capacity. The software used for the fracture-plastic model for reinforced concrete is ATENA.

Sign in / Sign up

Export Citation Format

Share Document