Magnetic non-destructive evaluation of ruptures of tensile armor in oil risers

Risers are flexible multilayered pipes formed by an inner flexible metal structure surrounded by polymer layers and spiral wound steel ligaments, also known as armor wires. Since these risers are used to link subsea pipelines to floating oil and gas production installations, and their failure could produce catastrophic consequences, some methods have been proposed to monitor the armor integrity. However, until now there is no practical method that allows the automatic non-destructive detection of individual armor wire rupture. In this work we show a method using magnetic Barkhausen noise that has shown high efficiency in the detection of armor wire rupture. The results are examined under the cyclic and static load conditions of the riser. This work also analyzes the theory behind the singular dependence of the magnetic Barkhausen noise on the applied tension in riser armor wires.

Niobium Effects on the Recrystallization Behavior on a Full Austenitic 15Cr-15Ni Stainless Steel Investigated Using Adaptive Neural Networks (ANN)

A new series of austenitic stainless steels-Nb stabilized, without Mo additions, non-susceptible to delta ferrite formation and devoid of intemetallic phases (sigma and chi), without deformation induced martensite is being developed, aiming at high temperature applications as well as for corrosive environments. The base steel composition is a 15Cr-15Ni with normal additions of Nb of 0.5, 1.0 and 2 wt%. Mechanical properties, oxidation and corrosion resistance already have been invetigated in previous papers. In this paper, the effects of Nb on the SFE, strain hardening and recrystallization resistance are evaluated with the help of Adaptive Neural Networks (ANN).

Influence of Alloying Elements Upon the Solidification Interval of CA6NM Cast Martensitic Stainless Steel

The influence of different Cr and C contents upon the solidification interval of ASTM A352M-06 Grade CA6NM cast martensitic stainless steel has been investigated using computational thermodynamics, and checked against DTA measurements in samples taken from 13 large cast parts, in order to identify potential sources for improvement on the part castability. Calculation results suggest, indeed, that this would be the case for C: when its content increases from 0.018 to 0.044 wt.% C (within the allowed range in the alloy specification), the solidification intervals increases from 25 to 43 K, which suggests improved castability with decreasing C contents. DTA results, however, do not support this prediction, showing a fairly constant solidification interval around 23 K for all investigated samples. The results are discussed both regarding the impact in alloy processing and the fitness of the existing databases to reproduce experimental results in these limiting cases.

Magnetic Barkhausen emission in lightly deformed AISI 1070 steel

The Magnetic Barkhausen Noise (MBN) technique can evaluate both micro- and macro-residual stresses, and provides indication about the relevance of contribution of these different stress components. MBN measurements were performed in AISI 1070 steel sheet samples, where different strains were applied. The Barkhausen emission is also analyzed when two different sheets, deformed and non-deformed, are evaluated together. This study is useful to understand the effect of a deformed region near the surface on MBN. The low permeability of the deformed region affects MBN, and if the deformed region is below the surface the magnetic Barkhausen signal increases. (C) 2011 Elsevier B.V. All rights reserved.

Tool wear evaluations in friction stir processing of commercial titanium Ti–6Al–4V

This research addresses the application of friction stir welding (FWS) of titanium alloy Ti–6Al–4V. Friction stir welding is a recent process, developed in the 1990s for aluminum joining; this joining process is being increasingly applied in many industries from basic materials, such as steel alloys, to high performance alloys, such as titanium. It is a process in great development and has its economic advantages when compared to conventional welding. For high performance alloys such as titanium, a major problem to overcome is the construction of tools that can withstand the extreme process environment. In the literature, the possibilities approached are only few tungsten alloys. Early experiments with tools made of cemented carbide (WC) showed optimistic results consistent with the literature. It was initially thought that WC tools may be an option to the FSW process since it is possible to improve the wear resistance of the tool. The metallographic analysis of the welds did not show primary defects of voids (tunneling) or similar internal defects due to processing, only defects related to tool wear which can cause loss of weld quality. The severe tool wear caused loss of surface quality and inclusions of fragments inside the joining, which should be corrected or mitigated by means of coating techniques on tool, or the replacement of cemented carbide with tungsten alloys, as found in the literature.

Issues on the mean stress effect in fretting fatigue of a 7050-T7451 Al alloy posed by new experimental data

The aims of this work are: (i) to produce new experimental data for fretting fatigue considering the presence of a mean bulk stress and (ii) to assess two design methodologies against failure by fretting fatigue. Tests on a cylinder–flat contact configuration were conducted using a fretting apparatus mounted on a servo-hydraulic machine. The material used for both the pads and fatigue specimen was an aeronautical 7050-T7451 Al alloy. The experimental program was designed with all relevant parameters, apart from the mean bulk load (always applied before the contact loads), kept constant. The mean bulk stress varied from compressive to tensile values while maintaining a high peak pressure in order to encourage crack initiation. Two methodologies against fretting fatigue are proposed and confronted against the experimental data. The non-local stress-based methodology considers the evaluation of a critical plane fatigue criterion at the center of a process zone located beneath the contacting surfaces. The results showed that it correctly predicts crack initiation, but was not capable to provide successful prediction of the integrity of the specimens. Alternatively, we considered a crack arrest criterion which has the potential to provide a more complete description about the integrity of the specimens.

Impact of thermal bridging on the performance of buildings using Light Steel Framing in Brazil

The Light Steel Framing building technology was introduced in Brazil in the late 1990s for the construction of residential houses. Because the design system was imported from the United States and is optimised to work well in that temperate climate, some modi fi cations must be made to adapt it for the Brazilian climate. The objective of this paper was to assess the impact of thermal bridging across enclosure elements on the thermal performance of buildings designed with Light Steel Framing in Brazil. The numerical simulation program EnergyPlus and a speci fi c method that considered the effects of metallic structures in the hourly simulations were used for the analysis. Two air-conditioned commercial buildings were used as case studies. The peak thermal load increased approximately 10% when an interior metal frame was included in the numerical simulations compared to non-metallic structures. Even when a metal frame panel was used only for vertical elements in the facade of a building with a conventional concrete structure, the simulations showed a 5% increase in annual energy use.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.