DTU Wind Energy developed a fast simulation approach to enable digital twins of large-scale structures

Significance 

The rapid development leap in digitalization increased the need for speed in order to unleash the full potential of digital twin technology by integrating structural health monitoring systems and real time fatigue-life prediction models on a full scale. That is to say, a high-fidelity method for efficient discrete fatigue crack growth simulation in large structures constitutes one of the cornerstones of a state-of-the-art digital twin.

In this context, discrete fatigue crack growth pertains to an insidious phenomenon during which a crack continues to inexorably propagate driven by the repeatedly applied loading cycles the structure experiences. Such fatigue cracks can remain undetected for a long period of time until structural failure occurs suddenly and without warning, making it reside among the most prominent root causes of catastrophic failure in wind turbines. This emphasizes the need for (1) a health monitoring system to detect the crack and with it (2) a fast fatigue lifetime prediction model to rapidly assess the severity of the situation. Whilst ‘fast and furious’ predictions are relatively easily achieved in the realm of discrete fatigue analysis, ‘fast and faithful’ is an entirely different story – an oxymoron of some sorts: In order to gain accuracy requires models with a high spatial discretization level – particularly in the vicinity of the crack – making them computationally heavy. Simultaneously, these models need to be re-executed several thousand times in order to update the crack position as it grows with sufficient temporal resolution. This inevitably compromises the computation speed inasmuch every attempt to increase the fidelity decreases the computation speed – and vice versa.

Against this backdrop, it can be agreed that the renaissance of digital twin technology heralded by recent advancements in machine learning raises the demand for structural analysis tools for real time predictions of the structural performance and ultimately the remaining lifetime. As such, there is a need to develop a technique to suffice this demand. In this view, researchers from the Department of Wind Energy at Technical University of Denmark: Dr. Martin Alexander Eder and Professor Xiao Chen, proposed a novel approach, termed FASTIGUE, for computationally super-efficient discrete fatigue crack growth analysis of large structures particularly for bondlines with high aspect ratios. Their goal was to considerably increase the computational efficiency by essentially decoupling the finite element analysis module from the crack growth analysis module. The research is now published in the Digital Twin Special Issue in the journal of Engineering Fracture Mechanics. https://doi.org/10.1016/j.engfracmech.2020.107075

In their approach, the computationally expansive analysis was performed prior to the fatigue analysis as a single pre-processing step for a comparatively small number of different fatigue crack propagation stages under the imposition of a set of qualified assumptions. The actual fatigue crack propagation analysis was then performed subsequently using an explicit crack growth simulation routine for a given set of growth parameters and initial crack situations in conjunction with the SERR functions previously obtained. Lastly, a practical demonstration of the proposed approach was applied to the fatigue growth analysis of a crack located in the trailing edge bondline of a 14.3 m long composite wind turbine blade model subject to flapwise cyclic loading.

In a statement to Advances in Engineering, Professor Xiao Chen pointed out by outsourcing the computationally expensive fracture analysis in a pre-processing step and by performing the crack growth prediction in a subsequent post-processing step, FASTIGUE outperforms conventional update-and-rerun schemes and offers unparalleled computation speed, making the digital twin concept of large scale structure close to reality.

The research is supported by DARWIN: Drone Application for pioneering Reporting in Wind turbine blade Inspections, Innovation Fund Denmark (6151-00020B) and RELIABLADE: Improving Blade Reliability through Application of Digital Twins over Entire Life Cycle, EUDP (64018-0068).

DTU Wind Energy developed a fast simulation approach to enable digital twins of large-scale structures - Advances in Engineering
FASTIGUE: predicting real-time fatigue life to unleash the full potential of digital twin technology of large-scale structures

About the author

Martin Alexander Eder (Researcher ID AAK-1213-2020) is presently a Senior Research Scientist at Technical University Denmark (DTU). After several years of international frontline work experience in industry, he earned his doctoral degree 2011 in earthquake engineering at Imperial College London and continued his work as a Postdoctoral Researcher at Imperial College before joining DTU Wind Energy in 2012. In 2018, he obtained another MSc degree in materials and manufacturing engineering at DTU.

Martin’s research interests pertain to both experimental and theoretical research in computational non-linear fracture mechanics of metals and composite materials, discrete and continuum damage based fatigue prediction methods, corrosion fatigue, elasticity and plasticity theory, non-prismatic beam theory, non-linear stability analysis of structures, advanced microstructure characterisation methods and novel approaches for component scale and full-scale testing methods. Martin has been project- and work-package leader of industrial research projects (EUDP) such as IMPACT and WindWeld. To date he has been main- and co-supervising industrial PhD students (Innovation Fund Denmark) and a Postdoc. He authored and co-authored more than 20 publications in a wide field of different applications.

About the author

Xiao Chen is currently an Associate Professor at Technical University of Denmark (DTU). He received his doctoral degree in structural engineering in 2011 from Nagoya University in Japan and then worked as a Postdoctoral Research Fellow in National Wind Energy Center at University of Houston, TX, US. From 2013, he was an Assistant Professor and later an Associate Professor at Chinese Academy of Sciences in Beijing before he joined DTU in 2017.

Xiao’s research field is experimental investigations and advanced numerical modeling of the structural response of large composite and offshore steel structures, with a primary focus on damages, failures and fractures driven by nonlinear buckling, multiple material failures, manufacturing-induced defects and extreme load conditions.

Xiao is currently the work package leader in the DARWIN project funded by the Innovation Fond of Denmark, the RELIABLADE project and the RELIFE project both supported by the Danish Energy Agency through the Energy Technology Development and Demonstration Program (EUDP). He is also the author of more than 20 journal articles and the supervisor of two Ph.D. students.

Reference

Martin Alexander Eder, Xiao Chen. FASTIGUE: A Computationally Efficient Approach for Simulating Discrete Fatigue Crack Growth in Large-scale Structures. Engineering Fracture Mechanics Volume 233, 2020, 107075.

Go To Engineering Fracture Mechanics

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