scholarly journals A Hybrid Surrogate Model for the Prediction of Solitary Wave Forces on the Coastal Bridge Decks

2021 ◽  
Vol 6 (12) ◽  
pp. 170
Author(s):  
Jinsheng Wang ◽  
Shihao Xue ◽  
Guoji Xu
Keyword(s):  
Solitary Wave ◽  
Hybrid Model ◽  
Surrogate Model ◽  
Bridge Decks ◽  
Wave Forces ◽  
Coastal Bridges ◽  
Modeling Techniques ◽  
Fast Development ◽  
Artificial Neural Network Ann ◽  
Prediction Capability

To facilitate the establishment of the probabilistic model for quantifying the vulnerability of coastal bridges to natural hazards and support the associated risk assessment and mitigation activities, it is imperative to develop an accurate and efficient method for wave forces prediction. With the fast development of computer science, surrogate modeling techniques have been commonly used as an effective alternative to computational fluid dynamics for the establishment of a predictive model in coastal engineering. In this paper, a hybrid surrogate model is proposed for the efficient and accurate prediction of the solitary wave forces acting on coastal bridge decks. The underlying idea of the proposed method is to enhance the prediction capability of the constructed model by introducing an additional surrogate to correct the errors made by the main predictor. Specifically, the regression-type polynomial chaos expansion (PCE) is employed as the main predictor to capture the global feature of the computational model, whereas the interpolation-type Kriging is adopted to learn the local variations of the prediction error from the PCE. An engineering case is employed to validate the effectiveness of the hybrid model, and it is observed that the prediction performance (in terms of residual mean square error and correlation coefficient) of the hybrid model is superior to the optimal PCE and artificial neural network (ANN) for both horizontal and vertical wave forces, albeit the maximum PCE degrees used in the hybrid model are lower than the optimal degrees identified in the pure PCE model. Moreover, the proposed hybrid model also enables the extraction of explicit predictive equations for the parameters of interest. It is expected that the hybrid model could be extended to more complex wave conditions and structural shapes to facilitate the life-cycle structural design and analysis of coastal bridges.

scholarly journals Review of wave forces on bridge decks with experimental and numerical methods

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Xuebin Chen ◽  
Zhiwu Chen ◽  
Guoji Xu ◽  
Xianrong Zhuo ◽  
Qinghua Deng
Keyword(s):  
Numerical Methods ◽  
Failure Mechanism ◽  
Bridge Deck ◽  
Numerical Models ◽  
Bridge Decks ◽  
Wave Force ◽  
Wave Forces ◽  
Coastal Zones ◽  
Coastal Bridges ◽  
Bridge Failure

AbstractMassive coastal bridges were damaged in Hurricanes Ivan (2004) and Katrina (2005), and considerable efforts have been devoted to the studies of wave forces acting on bridge decks since then. When the hurricane and tsunamis approach the coastal zones, the mean water level is elevated, making it possible for the incident wave to hit the bridge deck directly. The study of wave force acting on the bridge deck is essential for the investigation of bridge failure mechanism, and a literature review of wave forces with experimental and numerical methods after Hurricanes Ivan and Katrina is presented in this paper. Though the experiments and numerical models can not fully simulate the wave-deck interaction as in realistic conditions, remarkable progress has been achieved, and some significant findings help the researchers to further understand the failure mechanism of the bridge deck. Emphasis is given to the studies that have significantly improved our understanding of the topic. Challenges associated with the existing studies and suggestions for future studies are presented for a deeper understanding of the failure mechanism of the bridge deck, and more countermeasures are expected to protect the bridge deck under extreme wave forces.

EXPERIMENTAL STUDY OF WAVE FORCES ON BRIDGE DECKS

2009 ◽  
Author(s):  
Billy L. Edge ◽  
Ronald McPherson ◽  
Oscar Cruz-Castro
Keyword(s):  
Experimental Study ◽  
Bridge Decks ◽  
Wave Forces

scholarly journals A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures

2021 ◽  
Vol 7 ◽  
Author(s):  
Nikolaos Tsokanas ◽  
Xujia Zhu ◽  
Giuseppe Abbiati ◽  
Stefano Marelli ◽  
Bruno Sudret ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Hybrid Model ◽  
Surrogate Model ◽  
Global Sensitivity Analysis ◽  
Hybrid Simulation ◽  
Hybrid Models ◽  
Analysis Framework ◽  
Global Sensitivity ◽  
Sensitivity Indices ◽  
Realistic Situation

Hybrid simulation is an experimental method used to investigate the dynamic response of a reference prototype structure by decomposing it to physically-tested and numerically-simulated substructures. The latter substructures interact with each other in a real-time feedback loop and their coupling forms the hybrid model. In this study, we extend our previous work on metamodel-based sensitivity analysis of deterministic hybrid models to the practically more relevant case of stochastic hybrid models. The aim is to cover a more realistic situation where the physical substructure response is not deterministic, as nominally identical specimens are, in practice, never actually identical. A generalized lambda surrogate model recently developed by some of the authors is proposed to surrogate the hybrid model response, and Sobol’ sensitivity indices are computed for substructure quantity of interest response quantiles. Normally, several repetitions of every single sample of the inputs parameters would be required to replicate the response of a stochastic hybrid model. In this regard, a great advantage of the proposed framework is that the generalized lambda surrogate model does not require repeated evaluations of the same sample. The effectiveness of the proposed hybrid simulation global sensitivity analysis framework is demonstrated using an experiment.

Hybrid Neural Models For Rice Yields Times Forecasting

2012 ◽  
Author(s):  
Ruhaidah Samsudin ◽  
Puteh Saad ◽  
Ani Shabri
Keyword(s):  
Time Series ◽  
Hybrid Model ◽  
Moving Average ◽  
Time Series Prediction ◽  
Arima Model ◽  
Data Sets ◽  
Ann Model ◽  
Yield Data ◽  
Rice Yields ◽  
Artificial Neural Network Ann

In this paper, time series prediction is considered as a problem of missing value. A model for the determination of the missing time series value is presented. The hybrid model integrating autoregressive intergrated moving average (ARIMA) and artificial neural network (ANN) model is developed to solve this problem. The developed models attempts to incorporate the linear characteristics of an ARIMA model and nonlinear patterns of ANN to create a hybrid model. In this study, time series modeling of rice yield data in Muda Irrigation area. Malaysia from 1995 to 2003 are considered. Experimental results with rice yields data sets indicate that the hybrid model improve the forecasting performance by either of the models used separately. Key words: ARIMA; Box and Jenkins; neural networks; rice yields; hybrid ANN model

Experimental and numerical investigation of wave-current forces on coastal bridge superstructures with box girders

2019 ◽  
Vol 23 (7) ◽  
pp. 1438-1453 ◽  
Author(s):  
Jiawei Zhang ◽  
Bing Zhu ◽  
Azhen Kang ◽  
Ruitao Yin ◽  
Xin Li ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Numerical Models ◽  
Wave Forces ◽  
Vertical Force ◽  
Box Girder Bridges ◽  
Box Girder ◽  
Coastal Bridges ◽  
Girder Bridges ◽  
Wave Parameters ◽  
Waves And Currents

Coastal bridges are exposed to hurricane waves and storm surges during hurricanes, which threaten the safety of the superstructures. Since waves and ocean currents coexist in the natural marine environment and the action of currents leads to changes in wave parameters and thus affects wave loads, considering their interaction is necessary for the study of wave forces on coastal bridges. In this study, hydrodynamic loads on a box girder with the joint action of regular waves and currents are investigated with both experiments and numerical models. A series of experiments of wave forces that include conditions with different wave heights, current velocities, wave periods and submergence depths are conducted in a wave flume. Two-dimensional numerical simulations are performed to further investigate the mechanics of wave-current forces on box girder bridges. The wave parameters and wave forces of the numerical simulations are compared with the experimental results. The results indicate that a following current usually leads to higher maximum horizontal forces and lower maximum vertical forces. The opposing current results in a higher maximum hydrodynamic vertical force than following current with a low submergence depth. However, due to the joint effect of the wave parameters and structure position relationships, the behaviours of wave forces in other situations become complicated. It is anticipated that this study can provide experimental data of wave-current forces for the superstructures of box girder bridges and enhance the understanding of the mechanism of bridge damage by waves and currents.

scholarly journals Hybrid Models Combining Technical and Fractal Analysis with ANN for Short-Term Prediction of Close Values on the Warsaw Stock Exchange

2018 ◽  
Vol 8 (12) ◽  
pp. 2473 ◽  
Author(s):  
Michał Paluch ◽  
Lidia Jackowska-Strumiłło
Keyword(s):  
Hybrid Model ◽  
Fractal Analysis ◽  
Stock Prices ◽  
Stock Exchange ◽  
Hybrid Models ◽  
Fractal Modeling ◽  
Fractal Analyses ◽  
Warsaw Stock Exchange ◽  
Artificial Neural Network Ann ◽  
Short Term Prediction

This paper presents new methods and models for forecasting stock prices and computing hybrid models, combining analytical and neural approaches. First, technical and fractal analyses are conducted and selected stock market indices calculated, such as moving averages and oscillators. Next, on the basis of these indices, an artificial neural network (ANN) provides predictions one day ahead of the closing prices of the assets. New technical analysis indicators using fractal modeling are also proposed. Three kinds of hybrid model with different degrees of fractal analysis were considered. The new hybrid modeling approach was compared to previous ANN-based prediction methods. The results showed that the hybrid model with fractal analysis outperforms other models and is more robust over longer periods of time.

Effect of Entrapped Air on Solitary Wave Forces on a Coastal Bridge Deck with Girders

2016 ◽  
Vol 21 (2) ◽  
pp. 04015036 ◽  
Author(s):  
Betsy R. Seiffert ◽  
R. Cengiz Ertekin ◽  
Ian N. Robertson
Keyword(s):  
Solitary Wave ◽  
Bridge Deck ◽  
Wave Forces ◽  
Entrapped Air
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