Automated non-destructive integrity assessment of metal structures

Offshore windmills and pipeline networks are examples of strategic infrastructures used for the production of clean energy and for the storage and long-distance transportation of hydrocarbons, hydrogen and water. The relevant structural elements are mainly made of welded portions of steel pipes, which often interact with aggressive fluids and hostile environments. Material aging is thus accelerated and localized damage processes are promoted, harming the design safety factors. The structural health of such components can be monitored in operation, throughout their lifetime, by non-destructive testing performed by portable devices. The equipment at present available on the market permits to develop fully automated testing campaigns, overcoming the difficulties associated to large extension and difficult accessibility. The data collected on site can be transferred through virtual networks, to be evaluated and processed in order to permit the quantitative evaluations required by the optimization and the planning of repair and retrofit operations. This contribution discusses the potential offered by the current practice and illustrates the methodological adaptations that produce effective diagnostic tools in the outlined context

Machine Learning tools applied to the prediction and interpretation of the structural behavior of existing dams

The safety of existing dams is mainly ensured by the correct interpretation of monitoring data recorded during the whole lifetime of these structures. In this context, an increasing number of devices are being installed to provide more and more frequent measurements. Several Machine Learning tools have emerged as possible alternatives to traditional prediction approaches in recent years. Neural Networks have shown the ability to adapt to complex interactions and, therefore, to reach greater accuracy than conventional methods. However, this technique is susceptible to parameter tuning and difficult to generalize. Other recent studies have focused on Boosted Regression Trees. Less frequently used in dam engineering, they have proved to be equally accurate compared to Neural Networks, simpler to implement, and not sensitive to noisy and low relevant predictors. However, applications are limited to a few specific cases. The present contribution aims to evaluate the performances of this novel approach on dam data with a different specificity from previous research. The case study corresponds to a double-curvature arch dam introduced as a benchmark test by the International Commission on Large Dams. The input data include raw environmental variables, some derived variables, and time-related variables. Predictions of displacements under varying environmental conditions are performed, and relative influence indices are identified to determine the strength of each input-output relationship

Parametric failure analysis of metal-based composites

Metal-based composites can fail as a consequence of the growth and coalescence of micro-voids introduced with the manufacturing process. These detrimental phenomena influence the overall performance of the material to different extents since the macroscopic characteristics depend on both the local constitutive properties and geometry patterns, which promote various stress concentration and strain localization effects. The understanding of the different situations that arise in this context is often assisted by numerical simulations based on the GNT constitutive model, first proposed by Gurson (1977) and then refined by Needleman and Tvergaard (1984). However, exploring the influence of the most relevant material parameters on the composite response can be excessively time consuming. Therefore, traditional simulations based on non-linear finite element methods can be replaced by surrogate analytical approximations, which do not involve large computing costs but exhibit accuracy and sensitivity to the model parameters consistent with the practical applications. Some examples are presented in this contribution

An indentation based investigation on the characteristics of artificially aged pipeline steels

The decay of the mechanical properties of structural components operating in an aggressive environment can be detected by nondestructive indentation tests. The effectiveness of this approach has been verified on artificially aged pipeline steel. Indentation tests have been performed at different scales to verify the transferability of the laboratory results to the field conditions, in view of the possible development of in-situ diagnostic procedures

3D Scan of Hardness Imprints for the Non-destructive In-Situ Structural Assessment of Operated Metal Components

The structural integrity of operated components can be assessed by non-destructive mechanical tests performed in-situ with portable instruments. Particularly promising in this context are small scale hardness tests supplemented by the mapping of the residual imprints left on metal surfaces. The data thus collected represent the input of inverse analysis procedures, which determine the material characteristics and their evolution over time. The reliability of these estimates depends on the accuracy of the geometry scans and on the robustness of the data filtering and interpretation methodologies. The objective of the present work is to evaluate the accuracy of the 3D reconstruction of the residual deformation produced on metals by hardness tests performed at a few hundred N load. The geometry data are acquired by portable optical microscopes with variable focal distance. The imperfections introduced by the imaging system, which may not be optimized for all ambient conditions when used in automatic mode, are analysed. Representative examples of the output produced by the scanning tool are examined, focusing attention on the experimental disturbances typical of onsite applications. Proper orthogonal decomposition and data reduction techniques are applied to the information returned by the instrumentation. The essential features of the collected datasets are extracted and the main noise is removed. The results of this investigation show that the accuracy achievable with the considered equipment and regularization procedures can support the development of reliable diagnostic analyses of metal components in existing structures and infrastructures

Constitutive modelling and mechanical characterization of aluminium-based metal matrix composites produced by spark plasma sintering

Spark plasma sintering has been applied to the production of aluminium-based functionally graded material systems to be used in abrasive and high temperature conditions. The overall mechanical properties of these metal matrix composites were determined during the optimization phases of the production process by a fast and reliable identification procedure based on instrumented indentation, which can be easily performed on small specimens. The experimental information gathered from conical (Rockwell) indentation was used as input data for the calibration of the material parameters entering the elastic–plastic Drucker–Prager constitutive model. Eventually, the so identified material parameters were used to predict the result of pyramidal (Vickers) indentation, in order to validate the model selection and the output of the identification procedure. The good matching between modelling and experimental results for the different test configurations confirmed the soundness of the considered approach, especially evidenced on the light of the strong influence on the overall mechanical characteristics of the material microstructure and defectiveness resulting from the production process, which prevent the use of classical homogenization rules to evaluate the macroscopic material properties

Numerical simulation of non-standard tensile tests of thin metal foils

The evolution of the fracture processes occurring in thin metal foils can be evidenced by tensile tests performed on samples of non-standard dimensions. The load versus displacement record of these experiments does not return directly the local stress-strain relationship and the fracture characteristics of the investigated material. In fact, the overall response of thin foils is sensitive to local imperfections, size and geometric effects. Simulation models of the performed tests can support the interpretation of the experimental results, provided that the most significant physical phenomena are captured. The present contribution focuses on the role of modelling details on the numerical output that can be obtained in this context

Accuracy Check of Road’s Cross Slope Evaluation Using MMS Vehicle

Department of Civil Engineering (DCE), seat of Topography and Photogrammetry – Pisa University, cooperating with Excellence Centre for Telegeomatics Research of the Trieste University, is developing several methods in order to evaluate road’s cross slope. This measure is performed by use of instrumentation integrated on MMS vehicle GIGI One. In particular two different approaches are followed. The first one preview using of low cost monoaxial laser scanner IBEO Automotive LD GmbH, synchronized with Applanix POS LV system. With the second one cross slope is calculated by only inertial system data, using a simplified algorithm that describes vehicle dynamics. This paper will present an accuracy control of both methods. This control is realised on two different datasets, relating to the s.s. 58 Strada Nuova per Opicina, joining Trieste to Opicina and the s.s.1 Aurelia between Rosignano and Campolecciano, near Livorno. The control compares the two method’s results systematically and preview several single point check by tests realised with classic topographic instrumentation

Experimental and Numerical Analysis of Fracture in Prestressed Concrete

This work examines the crack initiation and propagation in Prestressed Concrete (PC) beams by a combined experimental and numerical approach. Four-point bending tests performed on PC sleepers lead to the formation of multiple cracks, in a number that depends on the specimen. The location of each fracture and its growth with time is monitored by Digital Image Correlation (DIC). The experiments are simulated by a finite element approach, reproducing the concrete response by a smeared crack model. The model parameters are calibrated to match the experimental moment deflection curve. In this study, only the beam segment enclosing one crack is discretized. The effect of the external load is simulated by applying the horizontal displacements returned by DIC at the vertical boundaries of the analyzed region. Thus, uncertainties are reduced since there is no need to discretize the PC element in its whole length, to include the supports and the loading plates, and to simulate the interactions between the different components

Characterization of fracture properties of thin aluminuminclusions embedded in anisotropic laminate composites

The fracture properties of thin aluminum inclusions embedded in anisotropic paperboardcomposites, of interest for food and beverage packaging industry, can be determined by performing tensile testson non-conventional heterogeneous specimens. The region of interest of the investigated material samples ismonitored all along the experiment by digital image correlation techniques, which allow to recover qualitativeand quantitative information about the metal deformation and about the evolution of the damaging processesleading to the detachment of the inclusion from the surrounding laminate composite. The interpretation of thelaboratory results is supported by the numerical simulation of the tests