• Energy Research
• civil engineering close
• European Commission close

The British railway system is the oldest in the world. Most railway embankments are aged around 150 years old and the percentage of disruption reports that feature them is frequently higher than other types of railway infrastructure. Remarkable works have been done to understand embankment deterioration and develop asset modelling. Nevertheless, they do not represent a sufficient way of managing assets in detail. As a result, reactive approaches combined with proactive ones would improve the whole asset management scenario. To guarantee good system performance, geotechnical asset management (GAM) aims to reduce uncertainty through informed, data driven decisions and optimisation of resources. GAM approaches are cost sensitive. Thus, data driven approaches that utilize existing resources are highly prized. Track geometry data has been routinely collected by Network Rail, over many years, to identify track defects and subsequently plan track maintenance interventions. Additionally, in 2018 Network Rail commissioned AECOM to undertake a study, described in this paper, to investigate the use of track geometry data in the detection of embankment instabilities. In this study, track geometry data for over 1800 embankments were processed and parameters offering the best correlation with embankment movements were identified and used by an algorithm to generate an embankment instability metric. The study successfully demonstrated that the instability of railway embankments is clearly visible in track geometry data and the metric gives an indication of the worsening of track geometry, that is likely due to embankment instability.

The British railway system is the oldest in the world. Most railway embankments are aged around 150 years old and the percentage of disruption reports that feature them is frequently higher than other types of railway infrastructure. Remarkable works have been done to understand embankment deterioration and develop asset modelling. Nevertheless, they do not represent a sufficient way of managing assets in detail. As a result, reactive approaches combined with proactive ones would improve the whole asset management scenario. To guarantee good system performance, geotechnical asset management (GAM) aims to reduce uncertainty through informed, data driven decisions and optimisation of resources. GAM approaches are cost sensitive. Thus, data driven approaches that utilize existing resources are highly prized. Track geometry data has been routinely collected by Network Rail, over many years, to identify track defects and subsequently plan track maintenance interventions. Additionally, in 2018 Network Rail commissioned AECOM to undertake a study, described in this paper, to investigate the use of track geometry data in the detection of embankment instabilities. In this study, track geometry data for over 1800 embankments were processed and parameters offering the best correlation with embankment movements were identified and used by an algorithm to generate an embankment instability metric. The study successfully demonstrated that the instability of railway embankments is clearly visible in track geometry data and the metric gives an indication of the worsening of track geometry, that is likely due to embankment instability.

This paper presents a general framework for estimating the state and unknown inputs at the level of a system subdomain using a limited number of output measurements, enabling thus the component-based vibration monitoring or control and providing a novel approach to model updating and hybrid testing applications. Under the premise that the system subdomain dynamics are driven by the unknown (i) externally applied inputs and (ii) interface forces, with the latter representing the unmodeled system components, the problem of output-only response prediction at the substructure level can be tailored to a Bayesian input-state estimation context. As such, the solution is recursively obtained by fusing a Reduced Order Model (ROM) of the structural subdomain of interest with the available response measurements via a Bayesian filter. The proposed framework is without loss of generality established on the basis of fixed- and free-interface domain decomposition methods and verified by means of three simulated Wind Turbine (WT) structure applications of increasing complexity. The performance is assessed in terms of the achieved accuracy on the estimated unknown quantities. Mechanical Systems and Signal Processing, 150 ISSN:0888-3270 ISSN:1096-1216

This paper presents a general framework for estimating the state and unknown inputs at the level of a system subdomain using a limited number of output measurements, enabling thus the component-based vibration monitoring or control and providing a novel approach to model updating and hybrid testing applications. Under the premise that the system subdomain dynamics are driven by the unknown (i) externally applied inputs and (ii) interface forces, with the latter representing the unmodeled system components, the problem of output-only response prediction at the substructure level can be tailored to a Bayesian input-state estimation context. As such, the solution is recursively obtained by fusing a Reduced Order Model (ROM) of the structural subdomain of interest with the available response measurements via a Bayesian filter. The proposed framework is without loss of generality established on the basis of fixed- and free-interface domain decomposition methods and verified by means of three simulated Wind Turbine (WT) structure applications of increasing complexity. The performance is assessed in terms of the achieved accuracy on the estimated unknown quantities. Mechanical Systems and Signal Processing, 150 ISSN:0888-3270 ISSN:1096-1216

The distortion of turbulence interacting with thick airfoils is analyzed with scale-resolved numerical simulations to elucidate its impact on leading-edge-noise generation and prediction. The effect of the leading-edge geometry is investigated by considering two airfoils with different leading-edge radii subjected to grid-generated turbulence. The velocity field is shown to be altered near the stagnation point, in a region whose extension does not depend on the leading-edge radius. Here, the deformation of large-scale turbulence causes the amplitude of the upwash velocity fluctuations to increase in the low-frequency range of the spectrum because of the blockage exerted by the surface. Conversely, the distortion of small-scale structures leads to an exponential decay of the spectrum at high frequencies due to the alteration of the vorticity field. The prevalence of a distortion mechanism over the other is found to depend on the size of the turbulent structures with respect to the curvilinear length from the stagnation point to the location where surface-pressure fluctuations and pressure gradient peak. This occurs at the curvilinear abscissa where the curvature changes the most. The same high-frequency exponential-decay slope observed for the upwash velocity is retrieved for surface-pressure spectra in the leading-edge region, suggesting that the airfoil unsteady response is induced by the distorted velocity field. This physical mechanism can be accounted for in Amiet's model by using a distorted turbulence spectrum as input and accounting for the increased amplitude of the distorted gust in the aeroacoustic transfer function, retrieving an accurate noise prediction for both airfoils.

The distortion of turbulence interacting with thick airfoils is analyzed with scale-resolved numerical simulations to elucidate its impact on leading-edge-noise generation and prediction. The effect of the leading-edge geometry is investigated by considering two airfoils with different leading-edge radii subjected to grid-generated turbulence. The velocity field is shown to be altered near the stagnation point, in a region whose extension does not depend on the leading-edge radius. Here, the deformation of large-scale turbulence causes the amplitude of the upwash velocity fluctuations to increase in the low-frequency range of the spectrum because of the blockage exerted by the surface. Conversely, the distortion of small-scale structures leads to an exponential decay of the spectrum at high frequencies due to the alteration of the vorticity field. The prevalence of a distortion mechanism over the other is found to depend on the size of the turbulent structures with respect to the curvilinear length from the stagnation point to the location where surface-pressure fluctuations and pressure gradient peak. This occurs at the curvilinear abscissa where the curvature changes the most. The same high-frequency exponential-decay slope observed for the upwash velocity is retrieved for surface-pressure spectra in the leading-edge region, suggesting that the airfoil unsteady response is induced by the distorted velocity field. This physical mechanism can be accounted for in Amiet's model by using a distorted turbulence spectrum as input and accounting for the increased amplitude of the distorted gust in the aeroacoustic transfer function, retrieving an accurate noise prediction for both airfoils.

Renewable energy is expected to experience epic growth in the coming decade, which is reflected in the record new installations since 2010. Wind energy, in particular, has proved its leading role among sustainable energy production means, by the accelerating rise in total installed capacity and by its consistently increasing trend. Taking a closer look at the history of wind power development, it is obvious that it has always been a matter of engineering taller turbines with longer blades. An increase in the tower height means an increase in the material used, thereby, impacting the initial construction cost and the total energy consumed. In the present study, a numerical investigation is carried out in order to actively compare conventional cylindrical shell towers with lattice towers in terms of material use, robustness and environmental impact. Lattice structures are proved to be equivalently competitive to conventional cylindrical solutions since they can be designed to be robust enough while being a much lighter tower in terms of material use. With detailed design, lattice wind turbine towers can constitute the new generation of wind turbine towers.