Scientific research
Our contribution to scientific research
We believe that cooperation is the key to innovation and technological development.
That is why we fully invest in scientific research and cooperate with universities and research centers to share knowledge and develop new technical capabilities.
Below you can read our scientific articles and publications
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Our scientific publications
Diamond-shaped steel lattice structural elements produced using Wire-Arc Additive Manufacturing: fabrication, experimental testing, and strength calibration
Steel lattice components produced using Wire-Arc Additive Manufacturing (WAAM) are emerging as a promising solution for the fabrication of lightweight, architecturally optimized structural elements; however, their behavior on a structural scale remains largely unexplored.
This study analyzes the structural response of diamond-shaped steel lattice elements (D-Poles) produced using WAAM and subjected to axial compression, providing the first comprehensive experimental dataset for this new class of components.
D-Poles consist of a repetition of diamond-shaped units (D-Chips) along their height and around a polygonal cross-section, resulting in continuous lattice elements with no discrete mechanical connections.
A manufacturing campaign was conducted using a WAAM robotic system with Cold Metal Transfer (CMT) technology, producing three-, four-, and six-sided D-Poles in three different heights (0.30 m, 0.60 m, and 0.90 m).
The specimens were characterized using industrial computed tomography to quantify their porosity and thickness distribution, and were subsequently subjected to monotonic compression tests on short and tall D-Poles.
The overall response appears to be governed by the flexural behavior of the D-Chips, rather than by a global instability phenomenon under peak load.
An analytical model was therefore adopted to interpret the yield and ultimate strength values and to develop a calibration—consistent with the Eurocodes—of the characteristic and design strength values.
Geometric Characterization of Steel Lattice Structures Produced by 3D Printing
Additive manufacturing (AM) technologies are opening up new possibilities for the production of complex metal geometries that are difficult to achieve using conventional processes. In this context, the Wire Arc Additive Manufacturing (WAAM) process shows significant potential for applications in civil engineering, thanks to its ability to produce large-scale metal components with a high degree of geometric freedom. This study focuses on Diamond elements, a new class of lattice elements consisting of Diamond unit cells, characterized by a regular polygonal base and inclined and vertical rods. These elements can be fabricated using the dot-by-dot WAAM strategy, which involves the sequential deposition of molten metal droplets. Manufacturing feasibility is demonstrated through the production of unit cells using WAAM. Since this process can generate geometric irregularities along rods and nodes—such as local defects, discontinuities, lack of straightness, and variations in cross-section—geometric characterization is essential for evaluating print quality and the severity of imperfections. To this end, a multi-level approach combining qualitative inspection and quantitative measurements is proposed. X-ray computed tomography and 3D scanning are used to reconstruct the as-built geometry and perform comparable measurements. Preliminary results, obtained on a single reticular cell produced using WAAM, demonstrate good geometric accuracy.
Hydrogen Embrittlement Resistance of an Optimized Additively Manufactured Austenitic Stainless Steel from Recycled Sources
In the framework of hydrogen production and storage for clean energy generation, the resistance to hydrogen embrittlement of a newly developed austenitic stainless steel is presented. Gas-atomized metal powders prepared from secondary-sourced metals were employed to manufacture test specimens with Laser Powder Bed Fusion (LPBF) technology. After machining and exposure to a controlled, pressurized hydrogen atmosphere at high temperature, the effect of hydrogen charging on the mechanical performance under static and dynamic conditions was investigated. The stabilizing effect of the optimized chemical composition is reflected in the absence of degradation effects on Yield Stress (YS), Ultimate Tensile Stress (UTS), and fatigue life observed for specimens exposed to hydrogen. Moreover, despite a moderate reduction in the elongation at fracture observed by increasing the hydrogen charging time, ductility loss calculated as Relative Reduction of Area (RRA) remains substantially unaffected by the duration of exposure to hydrogen and demonstrates that the austenitic steel is capable of resisting hydrogen embrittlement (HE).
Characterizing dot-by-dot steel waam bars using CT, 3D scanning and mechanical tests
This study focuses on the dot-by-dot deposition strategy in Wire Arc Additive Manufacturing (WAAM) technology, which consists of depositing molten metal droplets, creating line-type elements well-suited for largescale and complex lattice structures. The study analyzes the geometric irregularities and internal defects in bars with varying nominal diameters, build angles (inclination concerning the vertical axis), and printing parameters.
It evaluates their impact on mechanical performance via the results of Computed Tomography (CT) and highresolution 3D scanning. Mechanical tensile tests were performed on the bars to have an idea about the key mechanical parameters, enabling the evaluation of the influence of geometric irregularities on the mechanical performance.
Mitigation of human factor in tomographic post processing of additive manufactured critical parts for aviation application
Over the past decade, additive manufacturing (AM) has enabled the production of increasingly complex geometries, allowing designers to optimize components by integrating lattice structures, thick walls, and heat-dissipating geometries. However, these design advancements present challenges in inspection, as traditional non-destructive testing (NDT) methods have significant limitations. Techniques like Fluorescent Penetrant Inspection (FPI), Radiographic Testing (RT-2D), and Ultrasonic Testing (UT) face constraints due to surface roughness, positioning difficulties, and component geometry.
Industrial Computed Tomography (ICT) has emerged as the preferred NDT method for AM aerospace components due to its ability to inspect entire reconstructed volumes with optimized slicing techniques. As AM technology evolves, CT systems have also advanced, ranging from micro- and nano-focus systems for detecting micro-scale defects to linear accelerators for high-density alloy components.
Despite these advancements, a critical challenge remains: the significant cognitive load on technical personnel analyzing tomographic data. The extensive data volume and complexity of inspection methods increase stress, potentially leading to human factor-related issues, which are particularly critical in the aerospace industry.
This study aims to explore strategies for mitigating human factors in tomographic data post-processing for NDT applications, ultimately emphasizing the responsibility of inspectors in determining component serviceability.
Industrial Computed Tomography (ICT) has emerged as the preferred NDT method for AM aerospace components due to its ability to inspect entire reconstructed volumes with optimized slicing techniques. As AM technology evolves, CT systems have also advanced, ranging from micro- and nano-focus systems for detecting micro-scale defects to linear accelerators for high-density alloy components.
Despite these advancements, a critical challenge remains: the significant cognitive load on technical personnel analyzing tomographic data. The extensive data volume and complexity of inspection methods increase stress, potentially leading to human factor-related issues, which are particularly critical in the aerospace industry.
This study aims to explore strategies for mitigating human factors in tomographic data post-processing for NDT applications, ultimately emphasizing the responsibility of inspectors in determining component serviceability.
Despite these advances, a critical challenge persists: the high cognitive load required of technical personnel in tomographic data analysis. The sheer volume of data and the complexity of inspection methods add to the stress, with the risk of human factor phenomena, a particularly critical issue in aerospace.
This study aims to explore strategies to mitigate the impact of the human factor in post-inspection processing of tomographic data for NDT applications, focusing on the responsibility of inspectors in determining the suitability of components for service.
High Energy Computed Tomography of high-density alloys using a 6 MeV Linear Accelerator: detectability and use of Artificial Intelligence
In a sector not yet regulated like Additive Manufacturing, knowledge of the technology represents an important opportunity for companies that want to guarantee the quality of their 3D printing products. Furthermore, AM technologies are acquiring an increasing importance in the industrial production and in different fields, also using different materials, from polymeric to high density material such as Inconel. Components made by this technology could have complex geometries and the combination with high density materials can compromise both the capability and overall quality of the process. Industrial computed tomography is a widespread NDT technique that allows to perform a complete analysis, by combining dimensional inspection and a full volume defect control. At this point, it is important to define the limit of this technology in terms of detection of defects and geometries. This case study will focus on the first topic looking for the detectability of anomalies within the components made by Titanium alloy (TA6V) with high thickness, adding some considerations about possible use of an Artificial Intelligence (AI) based software, using a powerful source such as a Linear Accelerator. Many experiments have been performed through different CT analysis techniques, some of them carried out at high resolution on small samples made in Titanium alloy (TA6V) by additive manufacturing, looking for the real shape of designed defects. Then, a scan of these samples was performed using the LINAC system. Moreover, the use of a trained AI allows optimization of NDT process, thus reducing the influence of the human factor. The results showed the reliability of the technique and procedure used, given that it is possible to detect defects even in the worst analysis condition as in this case. These results consider both human factor and quality parameters of a CT system.
FEM Simulation of AlSi10Mg Artifact for Additive Manufacturing Process Calibration with Industrial-ComputedTomography Validation
A Study on the Use of XCT and FEA to Predict the Elastic Behavior of Additively Manufactured Parts of Cylindrical Geometry
Microwave assisted synthesis of Si-modified Mn25FexNi25Cu(50-x) high entropy alloys
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