Regularised Volterra series models for modelling of nonlinear self-excited forces on bridge decks

Volterra series models are considered an attractive approach for modelling nonlinear aerodynamic forces for bridge decks since they extend the convolution integral to higher dimensions. Optimal identification of nonlinear systems is a challenging task since there are typically many unknown variables that need to be determined, and it is vital to avoid overfitting. Several methods exist for identifying Volterra kernels from experimental data, but a large class of them put restrictions on the system inputs, making them infeasible for section model tests of bridge decks. A least-squares identification method does not restrict the inputs, but the identified model often struggles with noisy (non-smooth) kernels, which is deemed to be unphysical and a sign of overfitting. In this work, regularised least-squares identification is introduced to improve the performance of model identification using least-squares. Standard Tikhonov regularisation and other penalty techniques that impose decaying kernels are also explored. The performance of the methodology is studied using experimental data from wind tunnel tests of a twin deck section. The regularised Volterra models show equal or better results in terms of modelling the self-excited forces, and the regularisation makes the models less prone to overfitting

Nonlinear modelling of aerodynamic self-excited forces: An experimental study

The bridge aerodynamics research community is currently discussing several nonlinear wind load models for bridge decks, but no definite conclusion on which model is superior to the others is currently available. In this paper, we use experimental data for a double-deck section model tested in an advanced forced vibration rig to study the observed nonlinearities and to gain insight into what characteristics the nonlinear load model should be capable of modelling. Single harmonic horizontal, vertical and pitching motion; combined motion; and stochastic motion are considered. This approach allows the investigation of a more extensive range of nonlinear behaviours than regular wind tunnel testing. The typical nonlinear characteristics observed are mean drift, deviation from superposition and harmonic distortion. Further, we introduce a simple response-surface model for force prediction using polynomial combinations of the inputs and its derivatives. The model helps to gain further insight into the nonlinearity of the problem at hand and to select which refined modelling approach can be used in future work

A New Experimental Approach to Validation of Aerodynamic Derivatives Based Model for Self-Excited Forces

This paper was reviewed and accepted by the APCWE-IX Programme Committee for Presentation at the 9th Asia-Pacific Conference on Wind Engineering, University of Auckland, Auckland, New Zealand, held from 3-7 December 2017

The use of inverse methods for response estimation of long-span suspension bridges with uncertain wind loading conditions: Practical implementation and results for the Hardanger Bridge

Structural health monitoring (SHM) seeks to assess the condition or behaviour of the structure from measurement data, which for long-span bridges typically are wind velocities and/or structural vibrations. However, in the assessment of the wind-induced response effects, models for the actual loads must be adopted, which introduces uncertainties. An alternative is to apply model-based inverse methods that consider the input forces unknown, and estimate these forces jointly together with the system states using limited vibration data. This article presents a case study of implementing Kalman-type inverse methods to a long-span suspension bridge in complex terrain, with the objective of estimating the full-field response. Previous studies have shown the local wind field is complicated, leading to uncertain load effects. We discuss the key challenges faced in the use of the methodology for the long-span bridges and present the results for a six hour storm event. The analysis show that the dynamic response contribution from the 14 lowermost bridge modes (up to 3 rad/s or 0.5 Hz) can be reconstructed with decent accuracy. The estimated response magnitude differs from the predicted response from design specifications, pointing to initial load model uncertainties that can be reduced to give greater confidence in the assessment of wind-induced fatigue, wind-resistant performance or other response effects.Offshore Engineerin

Model-based force identification in experimental ice-structure interaction by means of Kalman filtering

The level-ice forces exerted on a scale model of a compliant bottom founded structure are identified from noncollocated strain and acceleration measurements by means of a joint input-state estimation algorithm. The identification is performed based on two different finite element models: one entirely based on the blueprints of the structure, and an updated one which predicts the first natural frequency more accurately. Results are presented for two different excitation scenarios characterized by the ice failure process and ice velocity, and known as the intermittent crushing and the continuous brittle crushing regimes. The accuracy of the identified forces is assessed by comparing them with those obtained by a frequency domain deconvolution on the basis of experimentally obtained frequency response functions. Results show a successful identification of the level-ice forces for both the intermittent and continuous brittle crushing regimes, even when significant modeling errors are present. The ice-induced displacements of the structure identified in conjunction with the forces are also compared to those measured during the experiment. These are found to be sensitive to the modelling errors in the blueprint model. By a simple tuning of the model, however, the estimated response is seen to match the measured one with high accuracy.Hydraulic EngineeringCivil Engineering and Geoscience

Impact of different biopolymer networks on the digestion of gastric structured emulsions

The deliberate design of food structures that impact on lipid digestion has received increasing attention because of the need for solutions to combat nutrition related concerns such as obesity and metabolic syndrome. In this study we examined how the hierarchical structure of foods can impact lipid digestion by incorporating gastric structuring emulsions in different biopolymer networks, namely i) a thermally reversible gelatine network, ii) a colloidal casein network, and iii) a concentrated starch particulate dispersion. The digestive breakdown of these emulsion filled biopolymer gels was followed by fat digestion kinetics in vitro and human clinical study (in vivo), rheological measurements and confocal laser scanning microscopy. The parent caseinate/monoglyceride (CasMag) stabilised emulsion underwent extensive partial coalescence upon exposure to gastric juice and as a result had very slow lipolysis (in vitro and in vivo). When the emulsion was incorporated within the biopolymer networks the rates of lipolysis were strongly correlated with the extent of partial coalescence of the CasMag emulsion, which was directly influenced by the structure and breakdown properties of each different biopolymer network. The way that biopolymer networks alter the digestion of the parent CasMag emulsion is likely affected by; i) how well the digestive juices mixed with the network/emulsion and, ii) the frequency and speed of droplet encounters, both of which have a direct impact on the ability of emulsions to undergo flocculation and (partial) coalescence. This knowledge may have important implications for the design and testing of real foods to understand and control the digestive behaviour of food nutrients.