Documents published in Scipedia

• Data-led Mechanical and Thermal Analysis of Layered Structures Based on Parametric Finite Element Analysis and Neural Network

  J. Ren

  eccomas2022.

  
  

  Abstract

  The mechanical and thermal behaviours of layered structures is of great importance for many advanced material systems and loading conditions. The responses of layered structures are controlled by the constitutive properties of each layer as well as the thicknesses. A comprehensive data-based approach is essential for both material analysis and design in direct or inverse problems. In this work parametric numerical modelling and Artificial Neural Network (ANN) are jointly used to develop data for layered structures. Mechanical and thermal finite element (FE) models are used to produce data for different material property and thickness domains. The use of ANN program is established and evaluated for different loading conditions. Using indentation as a typical case for mechanical loading and localized heating as typical example for thermal loading, ANN program was used to predict the behaviour of layered structures with different properties and layer thicknesses. Use of the data system in establishing dominating factors, synergetic effect on mechanical-thermal performance in advanced materials design is discussed.

  Abstract
  The mechanical and thermal behaviours of layered structures is of great importance for many advanced material systems and loading conditions. The responses of layered structures [...]

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• Explorative In-situ Analysis of Turbulent Flow Data Based on a Data-Driven Approach

  C. Gscheidle, J. Garcke

  eccomas2022.

  
  

  Abstract

  The Proper Orthogonal Decomposition (POD) has been used for several years in the post-processing of highly-resolved Computational Fluid Dynamics (CFD) simulations. While the POD can provide valuable insights into the spatial-temporal behaviour of single transient flows, it can be challenging to evaluate and compare results when applied to multiple simulations. Therefore, we propose a workflow based on data-driven techniques, namely dimensionality reduction and clustering to extract knowledge from large simulation bundles from transient CFD simulations. We apply this workflow to investigate the flow around two cylinders that contain complex modal structures in the wake region. A special emphasis lies on the formulation of in-situ algorithms to compute the data-driven representations during run-time of the simulation. This can reduce the amount of data inand output and enables a simulation monitoring to reduce computational efforts. Finally, a classifier is trained to predict characteristic physical behaviour in the flow only based on the input parameters.

  Abstract
  The Proper Orthogonal Decomposition (POD) has been used for several years in the post-processing of highly-resolved Computational Fluid Dynamics (CFD) simulations. While the [...]

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• Fluid-Structure Interaction Analyses of Amniotic Fluid with a Comprehensive Fetus Model Exposed to External Loading

  G. Kurgansky, J. Arias, E. Frankini, S. Echeverri, R. Chan-Akeley, M. Toma

  eccomas2022.

  
  

  Abstract

  A history of trauma during gestation is a risk factor for poor pregnancy outcomes. A multidisciplinary approach is vital to protect the mother's and the fetus' safety. Even though pregnancy-related trauma is uncommon, it is one of the leading causes of morbidity and mortality in pregnant women and fetuses. Hence, it is axiomatic to study the mechanism of the traumatic injuries to the fetus. The development of next-generation protective devices depends on our understanding of these mechanisms. Computational fluid-structure interaction simulations are used to study the effect of external loading on the fetus submerged in the amniotic fluid inside the uterus. A multitude of resulting variables is utilized to understand the cushioning function of the amniotic fluid on the fetus.

  Abstract
  A history of trauma during gestation is a risk factor for poor pregnancy outcomes. A multidisciplinary approach is vital to protect the mother's and the fetus' safety. [...]

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• Single-edge notched tension testing for assessing hydrogen embrittlement: a numerical study of test parameter influences

  R. Depraetere, M. Cauwels, W. De Waele, T. Depover, K. Verbeken, S. Hertelé

  eccomas2022.

  
  

  Abstract

  To evaluate the feasibility of the safe use of existing gas grids for the transport and storage of hydrogen gas, the phenomenon of hydrogen assisted degradation of steel used in the pipeline grid has to be examined. A finite element based framework developed for describing this phenomenon at the continuum scale is used to assist in the design and analysis of experimental characterisation of the tearing resistance. The framework is based on the complete Gurson model for ductile damage and takes into account damage acceleration due to the local hydrogen concentration, and the diffusion of hydrogen. Simulations representing single edge notched tension (SENT) fracture toughness tests of an API 5L X70 grade steel are performed and results are discussed in terms of crack growth resistance curves. Side grooves are included in the geometry of the SENT model to promote uniform crack growth. Different boundary conditions are employed, simulating ex-situ and in-situ hydrogen charging of specimens. Moreover, the effect of the applied deformation rate on the dynamics of hydrogen diffusion and the resulting toughness values is investigated. Accordingly, guidance regarding experimental SENT testing for the hydrogen assisted tearing resistance degradation is provided, in terms of test conditions (in-situ/ex-situ) and deformation rate.

  Abstract
  To evaluate the feasibility of the safe use of existing gas grids for the transport and storage of hydrogen gas, the phenomenon of hydrogen assisted degradation of steel used [...]

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• Design of integrated fluidic actuators for muti-axial loaded structural elements

  M. Bosch, M. Nitzlader, T. Burghardt, M. Bachmann, H. Binz, L. Blandini, M. Kreimeyer

  eccomas2022.

  
  

  Abstract

  The construction sector is responsible for high grey energy consumption and high greenhouse gas emissions. Adaptive structures can be a suitable solution to counteract this. Actuation of a beam to reduce the mass by counteracting the deflection with integrated fluidic actuators has been proven in previous studies. New challenges are brought about with the actuation of slabs due to the multi-axial load transfer. Many actuator principles are conceivable for this application. A combination of uniaxially acting actuators and complex designs that generate forces in different spatial directions in a targeted manner are possible. This paper presents various principles for the development of actuators integrated into the cross-section of a slab. These are able to manipulate the multi-axial load transfer behaviour directly. For this purpose, the actuator principles are classified according to various aspects. In a second step, numerical investigations are used to prove the effectiveness of the actuator principles.

  Abstract
  The construction sector is responsible for high grey energy consumption and high greenhouse gas emissions. Adaptive structures can be a suitable solution to counteract this. [...]

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• ARCHITECTURAL AND ENVIRONMENTAL IMPACT OF RETROFITTING TECHNIQUES TO PREVENT IN-PLANE ≪DOMINO≫ FAILURE MODES OF UNREINFORCED MASONRY BUILDINGS

  R. Liberotti, F. Cluni, F. Faralli, V. Gusella

  eccomas2022.

  
  

  Abstract

  The preservation of heritage buildings is not just about the structural safety, but it is necessarily related to the central themes of restoration, fruition and reuse of ancient buildings. Such topic requires an interdisciplinary design approach that involves, among the others, structural engineering, numerical modelling and architecture to address the challenges of contemporaneity in heritage management also in terms of interests of the stakeholders. In this regard, the opportunities offered by natural F.R.C.M. (Fibre Reinforced Cementitious Matrix) composites, made of basaltic fibres and lime mortar, are analysed.

  Abstract
  The preservation of heritage buildings is not just about the structural safety, but it is necessarily related to the central themes of restoration, fruition and reuse of ancient [...]

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• Effects of uncertainties of image-based material properties of great vessels on vascular deformation

  B. Fanni, M. Antonuccio, G. Santoro, A. Mariotti, M. Salvetti, S. Celi

  eccomas2022.

  
  

  Abstract

  Patient-specific computational models represent a powerful tool for the planning of cardiovascular interventions. In this context, the patient-specific material properties are considered as one of the biggest source of uncertainty. In this work, we investigated the effect of the uncertainty of the elastic module (E), as computed from a recent image-based methodology, on a fluid-structure interaction (FSI) model of a patientspecific aorta. The Uncertainty Quantification (UQ) was carried out using the generalized Polynomial Chaos (gPC) method. Four deterministic simulations were run based on the four quadrature points, computed considering a deviation of ±20% on the estimation of the E value of the vessel wall from patient's imaging. The UQ of the E parameter was evaluated on the area and flow variations among cardiac cycle extracted from five cross-sections of the aortic FSI model. Results from gPC analysis showed a not significant variation of the area and flow quantities during the whole cardiac period, thus demonstrating the effectiveness of the used image-based methodology in the inferring of the E parameter, despite its intrinsic errors due to model definition. This study highlights the importance of imaging to retrieve useful data in an indirect and noninvasive way, to enhance the reliability of in-silico models in the clinical practice.

  Abstract
  Patient-specific computational models represent a powerful tool for the planning of cardiovascular interventions. In this context, the patient-specific material properties [...]

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• Quantification of time-averaging uncertainties in turbulence simulations

  D. Xavier, S. Rezaeiravesh, R. Vinuesa, P. Schlatter

  eccomas2022.

  
  

  Abstract

  An automatic method is proposed for the removal of the initialization bias that is intrinsic to the output of any statistically stationary simulation. The general techniques based on optimization approaches such as Beyhaghi et al. [1] following the Marginal Standard Error Rules (MSER) method of White et al. [16] were observed to be highly sensitive to the fluctuations in a time series and resulted in frequent overprediction of the length of the initial truncation. As fluctuations are an innate part of turbulence data, these techniques performed poorly on turbulence quantities, meaning that the local minima was often wrongly interpreted as the minimum variance in the time series and resulted in different transient point predictions for any increments to the sample size. This limitation was overcome by considering the finite difference of the slope of the variance computed in the optimization algorithm. The start of the zero slope region was considered as the initial transient truncation point. This modification to the standard approach eliminated the sensitivity of the scheme, and led to consistent estimates of the transient truncation point, provided that the finite difference time interval was chosen large enough to cover the fluctuations in the time series. Therefore, the step size for the finite difference slope was computed using both visual inspection of the time series and trial and error. We propose the Augmented Dickey­Fuller test as an automatic and reliable method to determine the truncation point, from which the time series is considered stationary and without an initialization bias.

  Abstract
  An automatic method is proposed for the removal of the initialization bias that is intrinsic to the output of any statistically stationary simulation. The general techniques [...]

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• Classification of compromised DOFS data with LSTM neural networks

  V. Usenco, K. Lasn

  eccomas2022.

  
  

  Abstract

  Distributed optical fiber sensors (DOFS) are gaining momentum for in-situ condition monitoring and damage detection purposes. Although DOFS are a versatile sensing method enabling high-resolution strain and temperature mapping, they are also sensitive to mechanical vibrations. Vibrations are typically created by the ambient environment (e.g acoustic background, rotating equipment) which can produce high levels of measurement noise. With physical access to DOFS installations, the principle of acoustic or mechanical vibrations can also be utilized for malicious sensor tampering. The current lack of anomaly-detection systems suggests that practical DOFS applications would benefit from an automated analysis to detect and classify compromised measurements. Noise classification makes it possible to identify its source and potentially remove its effects from the measurement in the future. This would expand the commercial applications of DOFS systems significantly. Neural networks have been used for error detection in cyber-physical applications in numerous studies with high-accuracy results. Specifically, long short-term memory (LSTM) neural network models have become popular in recent years to classify anomalies in sequential e.g time-series data. Our investigation conducted a series of physical experiments using magnitude-controlled mechanical disturbances on bare free-hanging DOFS. Both random low-frequency vibrations at large displacement amplitudes and a constant high-frequency acoustic source at a low amplitude were employed. Experiments revealed that strain patterns are visually different with varying types and levels of disturbances. For the numerical analysis, statistics and machine learningbased approaches were applied for DOFS vibration noise classification, and their accuracy is discussed in detail. Results from the post-processing of compromised DOFS data suggest that it is possible to develop a vibration detection or classification system based on off-the-shelf DOFS interrogation equipment coupled with LSTM numerical tools.

  Abstract
  Distributed optical fiber sensors (DOFS) are gaining momentum for in-situ condition monitoring and damage detection purposes. Although DOFS are a versatile sensing method [...]

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• Multiscale finite element modeling linking shell elements to 3D continuum

  D. Addessi, P. Di Re, C. Gatta, E. Sacco

  eccomas2022.

  
  

  Abstract

  The present paper investigates the response of masonry structural elements with periodic texture adopting an advanced multiscale finite element model, coupling different formulations at the two selected scales of analysis. At the macroscopic structural level, a homogeneous thick shell is considered and its constitutive response is derived by the detailed analysis of the masonry repetitive Unit Cell (UC), analyzed at the microlevel in the framework of the threedimensional (3D) Cauchy continuum. The UC is formed by the assembly of elastic bricks and nonlinear mortar joints, modeled as zero-thickness interfaces. The Transformation Field Analysis procedure is invoked to address the nonlinear homogenization problem of the regular masonry. The performance of the model in reproducing various masonry textures is explored by referring to an experimentally tested pointed vault under different profiles of prescribed differential settlements. The structural behavior of the vault is studied in terms of global load-displacement curves and damaging patterns and the numerical results are compared with those recovered by detailed micromechanical analyses and experimental evidences.

  Abstract
  The present paper investigates the response of masonry structural elements with periodic texture adopting an advanced multiscale finite element model, coupling different formulations [...]

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