Behaviour of stainless and high strength steel bolt assemblies at elevated temperatures — A review

Shaheen, Mohamed A.; Foster, A.S.J.; Cunningham, Lee S.; Afshan, Sheida

doi:10.1016/j.firesaf.2020.102975

Cited by 30 publications

(12 citation statements)

References 49 publications

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“…SPE causes surface damage to a component quickly, which lowers the structural integrity of the machine parts [15]. The mechanical surface degradation further compromises the component survival [16]. So, a thorough literature review for SPE is carried out.…”

Section: Literature Reviewmentioning

confidence: 99%

Solid particle erosion behavior of nichrome coated duplex stainless steel

2022

IJATEE

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One of the most serious concerns for the industry is material degradation, which leads to premature failure. Solid particle erosion (SPE) is a significant material degradation phenomenon. To be more specific, the erosion problem is made worse by the fluid inclusion of gravel and other contaminants. Despite being well studied and predicted, the process of solid particle erosion is still not properly known. Therefore, additional experimental research is still required to properly understand the erosion process and offer novel erosion resistance strategies. Employing coatings is the most effective technique to reduce/prevent solid particle erosion. The most commonly used methods to improve erosion resistance are proper material selection and the application of coatings. The erosion behaviour of atmospheric plasma-coated Nichrome (NiCr) on coated and uncoated duplex stainless steel (DSS2205) substrates were investigated. The erosion test is performed using an air-jet erosion tester with alumina as the erodent at velocities of 150, 175 and 200 m/s, impact angles of 30°,45° and 90°, and discharge rates of 2.5, 3.75 and 5 gm/min. This study discovered that the most influential factors of erosion are impact angle. When the impact angle is 90°, the velocity is 150 m/s, and the discharge rate is 5 gm/min, the erosion was minimal. Analysis of the surface microstructure reveals many erosion mechanisms linked to various incidence angles. The erosion mechanism changes from micro-ploughing to plastic deformation for low to high impactangles. Furthermore, metallographic examinations are used in conjunction with the experimental results. As per the experimental findings, coating bare substrates with NiCr can substantially increase erosion resistance. Moreover, NiCr coatings on bare substrates showed a 47% reduction in erosion wear, primarily as a result of their better toughness, higher density, improved micro-hardness, and lower porosity.

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Section: Literature Reviewmentioning

confidence: 99%

Solid particle erosion behavior of nichrome coated duplex stainless steel

2022

IJATEE

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“…It has been observed that, in the case of moment connections, the tensile force in the bolts tends to decrease with increasing temperature. However, in the case of shear connections, the force in the bolts tends to increase with temperature [44]. At elevated temperatures, the mechanical properties of the bolts also drop significantly, which directly affects the safety and reliability of steel structures [3,34,53].…”

Section: Introductionmentioning

confidence: 99%

Thermal strength analysis of a steel bolted connection under bolt loss conditions

Grzejda¹

2022

Eksploatacja i Niezawodność – Maintenance and Reliability

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The aim of the paper is to analyse an exemplary bolted connection under the conditions of loss of bearing capacity of some fasteners in the connection. The presented tests are numerical and concern an asymmetric bolted connection. The joined elements in the connection were modelled as 3D finite elements, and the fasteners were treated as hybrid models consisting of rigid heads and nuts, and flexible beams between them. The bolted connection was first preloaded according to six different tensioning orders using a standardised force. After all bolts were tensioned, the selected bolts were removed, simulating bolt damage. The connection was then tested for external loads with temperatures ranging from 20 to 600°C. The influence of loosening the connection on the load in the remaining bolts at the operational stage of the connection was investigated. The calculation results were compared with the test results for a healthy bolted connection. It was shown that the bearing capacity of the connection in the damaged state decreased by 13%.

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“…Although the automated detection process based on image processing and machine learning techniques offered great benefits it has some major drawbacks. One of the most significant is that the appearance of abnormalities changes in terms of form, size, colour, geometry, and other factors even within the same inspection work [15]. Due to these reasons computer vision applications and deep learning based convolution neural network (CNN) can be used for better efficiency and precise detection rate.…”

Section: Introductionmentioning

confidence: 99%

Taguchi based Design of Sequential Convolution Neural Network for Classification of Defective Fasteners

Kaur¹,

Chauhan²,

Aggarwal³

et al. 2022

Preprint

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Fasteners play a critical role in securing various parts of machinery. Deformations such as dents, cracks, and scratches on the surface of fasteners are caused by material properties and incorrect handling of equipment during production processes. As a result, quality control is required to ensure safe and reliable operations. The existing defect inspection method relies on manual examination, which consumes a significant amount of time, money, and other resources; also, accuracy cannot be guaranteed due to human error. Automatic defect detection systems have proven impactful over the manual inspection technique for defect analysis. However, computational techniques such as convolutional neural networks (CNN) and deep learning-based approaches are evolutionary methods. By carefully selecting the design parameter values, the full potential of CNN can be realised. Using Taguchi based design of experiments and analysis, an attempt has been made to develop a robust automatic system in this study. The dataset used to train the system has been created manually for M14 size nuts having two labeled classes: Defective and Non-defective. There are a total of 264 images in the dataset. The proposed sequential CNN comes up with a 96.3% validation accuracy, 0.277 validation loss at 0.001 learning rate.

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Behaviour of stainless and high strength steel bolt assemblies at elevated temperatures — A review

Cited by 30 publications

References 49 publications

Solid particle erosion behavior of nichrome coated duplex stainless steel

Solid particle erosion behavior of nichrome coated duplex stainless steel

Thermal strength analysis of a steel bolted connection under bolt loss conditions

Taguchi based Design of Sequential Convolution Neural Network for Classification of Defective Fasteners

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