Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges

As important links in the transport infrastructure system, cable-stayed bridges are among the most popular candidates for implementing structural health monitoring (SHM) technology. The primary aim of SHM for these bridges is to ensure their structural integrity and satisfactory performance by monitoring their behaviour over time. Finite element (FE) model updating is a well-recognised approach for SHM purposes, as an accurate model serves as a baseline reference for damage detection and long-term monitoring efforts. One of the many challenges is the development of the initial FE model that can accurately reflect the dynamic characteristics and the overall behaviour of a bridge. Given the size, slenderness, use of long cables, and high levels of structural redundancy, precise initial models of long-span cable-stayed bridges are desirable to better facilitate the model updating process and to improve the accuracy of the final updated model. To date, very few studies offer in-depth discussions on the modelling approaches for cable-stayed bridges and the methods used for model updating. As such, this article presents the latest advances in finite element modelling and model updating methods that have been widely adopted for cable-stayed bridges, through a critical literature review of existing research work. An overview of current SHM research is presented first, followed by a comprehensive review of finite element modelling of cable-stayed bridges, including modelling approaches of the deck girder and cables. A general overview of model updating methods is then given before reviewing the model updating applications to cable-stayed bridges. Finally, an evaluation of all available methods and assessment for future research outlook are presented to summarise the research achievements and current limitations in this field.

A Review of Modelling of the FCC Unit. Part I: The Riser

Heavy petroleum industries, including the fluid catalytic cracking (FCC) unit, are useful for producing fuels but they are among some of the biggest contributors to global greenhouse gas (GHG) emissions. The recent global push for mitigation efforts against climate change has resulted in increased legislation that affects the operations and future of these industries. In terms of the FCC unit, on the riser side, more legislation is pushing towards them switching from petroleum-driven energy sources to more renewable sources such as solar and wind, which threatens the profitability of the unit. On the regenerator side, there is more legislation aimed at reducing emissions of GHGs from such units. As a result, it is more important than ever to develop models that are accurate and reliable, that will help optimise the unit for maximisation of profits under new regulations and changing trends, and that predict emissions of various GHGs to keep up with new reporting guidelines. This article, split over two parts, reviews traditional modelling methodologies used in modelling and simulation of the FCC unit. In Part I, hydrodynamics and kinetics of the riser are discussed in terms of experimental data and modelling approaches. A brief review of the FCC feed is undertaken in terms of characterisations and cracking reaction chemistry, and how these factors have affected modelling approaches. A brief overview of how vaporisation and catalyst deactivation are addressed in the FCC modelling literature is also undertaken. Modelling of constitutive parts that are important to the FCC riser unit such as gas-solid cyclones, disengaging and stripping vessels, is also considered. This review then identifies areas where current models for the riser can be improved for the future. In Part II, a similar review is presented for the FCC regenerator system.

Impact of Modelling Approach on the Estimation of Government Intervention Effects in COVID-19

The efficacy of government interventions in epidemic has become a hot subject since the onset of COVID-19. There is however much variation in the results quantifying the effects of interventions, which is partly related to the varying modelling approaches employed by existing studies. This paper therefore aims to examine how the choice of modelling approach would affect the estimation results of intervention effects, by experimenting with different modelling approaches on a same data set composed of the 500 most affected U.S. counties. We compare the most frequently used methods from the two classes of modelling approaches, which are Bayesian hierarchical model from the class of computational approach and difference-in-difference from the class of natural experimental approach. We find that computational methods are likely to produce larger estimates of intervention effects due to simultaneous voluntary behavioral changes. In contrast, natural experimental methods are more likely to extract the true effect of interventions. Among different difference-in-difference estimators, the two-way fixed effect estimator seems to be an efficient one. Our work can inform the methodological choice of future research on this topic, as well as more robust re-interpretation of existing works, to facilitate both future epidemic response plans and the science of public health.