Felice Rubino

Selective Laser Post-Treatment on Titanium Cold Spray Coatings

The aim of the present work is to investigate the feasibility and effects of a selective postdeposition laser treatment on titanium coatings. Commercially pure titanium grade 2 powders were deposited by means of a cold spray process on aluminum alloy AA2024-T3 sheets. The surface treatment of the coating was realized using a 220 W diode laser. The influence of heat input and dimensional features of coating layer and substrate was assessed by an experimental campaign conducted following a design of experiments approach. Optical and scanning electron microscopy analysis of the microstructure of the deposited and treated material as well as microhardness measurements showed the formation of a compact layer of titanium oxide on the coating surface and the preservation of the temper state of the aluminum substrate.

Selective Laser Treatment on Cold-Sprayed Titanium Coatings: Numerical Modeling and Experimental Analysis

In this paper, a selective laser post-deposition on pure grade II titanium coatings, cold-sprayed on AA2024-T3 sheets, was experimentally and numerically investigated. Morphological features, microstructure, and chemical composition of the treated zone were assessed by means of optical microscopy, scanning electron microscopy, and energy dispersive X-ray spectrometry. Microhardness measurements were also carried out to evaluate the mechanical properties of the coating. A numerical model of the laser treatment was implemented and solved to simulate the process and discuss the experimental outcomes. Obtained results highlighted the key role played by heat input and dimensional features on the effectiveness of the treatment.

Microstructural Aspects in FSW and TIG Welding of Cast ZE41A Magnesium Alloy

In this paper, magnesium ZE41A alloy plates were butt joined through friction stir welding (FSW) and Tungsten Inert Gas welding processes. Process-induced microstructures were investigated by optical and SEM observations, EDX microanalysis and microhardness measurements. The effect of a post-welded T5 heat treatment on FSW joints was also assessed. Sound joints were produced by means of both techniques. Different elemental distributions and grain sizes were found, whereas microhardness profiles reflect microstructural changes. Post-welding heat treatment did not induce significant alterations in elemental distribution. The FSW-treated joint showed a more homogeneous hardness profile than the as-welded FSW joint.

Hard and soft computing models of composite curing process looking toward monitoring and control

The curing process of thermosetting resins plays a key role on the final quality of the composite material components. Soft computing techniques proved to be an efficient method to control and optimize the curing process, replacing the conventional experimental and numerical approaches. In this paper artificial neural network (ANN) and fuzzy logic control (FLC) were implemented together to predict and control the temperature and degree of cure profile during the autoclave curing process. The obtained outcomes proved the capability of ANNs and FLC with respect to the hard computing methods.

Thermo-chemical, mechanical and resin flow integrated analysis in pultrusion

The present work discusses some numerical outcomes provided by an integrated analysis of impregnation, thermo-chemical and stress/strain aspects in a conventional pultrusion process. The impregnation models describes resin flow and pressure distribution in the initial portion of the die, solving a non-homogeneous non-isothermal/reactive multiphase problem, using a finite volume scheme. The thermochemical model describes the heat transfer and degree of cure evolution of the processing resin. Finally, the stress/strain model computes the part distortion and in process stresses due to thermal, chemical, mechanical strains. An applicative case study is presented, simulating the impregnation step of the pultrusion process of a fiberglass-epoxy resin composite rod.

Advances in Titanium on Aluminium Alloys Cold Spray Coatings

Cold gas dynamic spraying (CGDS) is an emerging technique that involves the surface modification in order to provide enhanced surface properties on material substrates. Particles, with size in the range of 1–50 μm, are accelerated by a supersonic jet gas up to 1200 m/s and impact on the substrate surface. Under specific conditions, the metal powders undergo a severe plastic deformation and adhere to the substrate. In the last decades, the cold spraying of several materials, like copper, aluminium and iron, has been widely explored providing optimal processing windows for a wide range of material pairs. Titanium and its alloys are finding a widespread use in many strategic industries, namely, aeronautic and aerospace field, due to the lightweight, high corrosion resistance and compatibility with polymer-reinforced composites, as well as in the biomedical sector, due to their biocompatibility. However, the high cost of raw materials and the manufacturing issues put severe restrictions to their wider use. On the other hand, replacement of titanium bulk with multilayer material, consisting in a cold sprayed titanium coating on aluminium components, could be a promising alternative and an advantageous trade-off between the cost compression and the higher surface properties of titanium alloy. The present chapter deals with the analysis of the deposition of pure titanium coatings on aluminium alloy substrate by means of low-pressure cold gas spray technique and deals also with the study of the properties of multilayer material. A post-deposition process to further improve the properties of the coating itself was also analysed.

Neural-fuzzy optimization of thick composites curing process

ABSTRACT This article addresses the optimization of curing process for thick composite laminates. The proposed methodology aims at the evaluation of the thermal cycle promoting a desired evolution of the degree of cure inside the material. At the same time, temperature overshooting as well as excessive temperature and cure degree gradient through the thickness of the material are prevented. The developed approach is based on the integrated application of artificial neural networks and a fuzzy logic controller. The neural networks promptly predict the behavior of composite material during curing process, while the fuzzy logic controller continuously and opportunely adjusts the proper variations on the imposed thermal cycle. The results highlighted the efficiency of the method in comparison with the cure profiles dictated by the material suppliers. For thick laminates, a reduction of 35% of cure time and improvements of approximately 10% of temperature overshooting was obtained compared to conventional curing cycles. The method was validated by experimental tests.

Artificial Neural Networks in Advanced Thermoset Matrix Composite Manufacturing

Autoclave curing is a common practice to manufacture high temperature thermoset matrix composites. The cycle design and optimization of the temperature-time curve is a key issue for a competitive production. In this paper artificial neural networks (ANN), as a technique of artificial intelligence, were used for prediction of the composite temperature profile during the autoclave curing process. Different neural network models have been investigated regarding their capabilities for prediction of the composite temperature profile. The new neural network model has been developed able to predict the composite temperature profile in the wide range of manufacturing conditions changing.

Strain and temperature measurement in pultrusion processes by fiber Bragg grating sensors

Injection Pultrusion (IP) is one of the most effective processes, in terms of productivity and costs, to manufacture fiber reinforced polymers. In IP roving of fiber are driven through an injection chamber in which they are impregnated by the resin and then formed in a shaped die. The die is heated in order to cure the resin. Pultruded products are in most cases characterized by constant cross-section profile, whereas unidirectional long fibers are mainly used as reinforcing material. Two relevant phenomena occur within the injection chamber and the heated die, namely the impregnation of the fibers and the polymerization of the resin. Furthermore, thermal expansion, resin chemical shrinkage and the interaction between the die and the impregnated fibers strongly influence the process [1]. Clearly, thermal and mechanical fields significantly impact on these strictly chained behaviours. The use of thermocouples to evaluate temperature within pultrusion die is already widespread, but they are not capable to acquire any information concerning stress-strain levels. In the present work Fibers Bragg Gratings (FBG) sensors were used to measure thermal and strain profiles in selected material location within the injection chamber and the curing die. Being the differences among the spectres transmitted and received are related to the variations in both temperature and strain, commercial FBG sensors were opportunely modified and calibrated. The optical fibers were hooked to the fibers entering into the injection pultrusion die. Taking the pulling speed into account, each waveform acquired was correlated to a position within the die. Obtained data highlight the effect of the heat generation due to resin reaction as well as longitudinal strains related to the pulling force, the thermal expansion and the chemical shrinkage of the resin system.Injection Pultrusion (IP) is one of the most effective processes, in terms of productivity and costs, to manufacture fiber reinforced polymers. In IP roving of fiber are driven through an injection chamber in which they are impregnated by the resin and then formed in a shaped die. The die is heated in order to cure the resin. Pultruded products are in most cases characterized by constant cross-section profile, whereas unidirectional long fibers are mainly used as reinforcing material. Two relevant phenomena occur within the injection chamber and the heated die, namely the impregnation of the fibers and the polymerization of the resin. Furthermore, thermal expansion, resin chemical shrinkage and the interaction between the die and the impregnated fibers strongly influence the process [1]. Clearly, thermal and mechanical fields significantly impact on these strictly chained behaviours. The use of thermocouples to evaluate temperature within pultrusion die is already widespread, but they are not capable to a...

Flow monitoring of microwave pre-heated resin in LCM processes

Liquid composite molding is manufacturing techniques that involve the injection or infusion of catalyzed liquid resin into a mold to impregnate a dry fiber preform. The challenges of LCM processes are related to the obtaining of a complete wetting of the reinforcement as well as a reduction of the void to obtain a final product with high mechanical properties. The heating of the resin prior the injection into the mold cavity has proven to be useful to improve the LCM processes. The increasing of temperature results in a reduction of resin viscosity and allows the resin to flow more easily through the reinforcement; the cure stage is also improved resulting in a reduction of global process time required. Besides the conventional solutions to heat up the resin based on the thermal conduction, in-line microwave heating is a suitable method to heat dielectric materials providing an even temperature distribution through the resin, thereby avoiding a thermal gradient between the surface and the core of liquid r...