Determination Of Stress Concentration Factors Research Articles

An artificial neural network model for determining stress concentration factors for fatigue design of tubular T-joint under compressive loads

PurposeThe stress concentration factor (SCF) is commonly utilized to assess the fatigue life of a tubular T-joint in offshore structures. Parametric equations derived from experimental testing and finite element analysis (FEA) are utilized to estimate the SCF efficiently. The mathematical equations provide the SCF at the crown and saddle of tubular T-joints for various load scenarios. Offshore structures are subjected to a wide range of stresses from all directions, and the hotspot stress might occur anywhere along the brace. It is critical to incorporate stress distribution since using the single-point SCF equation can lead to inaccurate hotspot stress and fatigue life estimates. As far as we know, there are no equations available to determine the SCF around the axis of the brace.Design/methodology/approachA mathematical model based on the training weights and biases of artificial neural networks (ANNs) is presented to predict SCF. 625 FEA simulations were conducted to obtain SCF data to train the ANN.FindingsUsing real data, this ANN was used to create mathematical formulas for determining the SCF. The equations can calculate the SCF with a percentage error of less than 6%.Practical implicationsEngineers in practice can use the equations to compute the hotspot stress precisely and rapidly, thereby minimizing risks linked to fatigue failure of offshore structures and assuring their longevity and reliability. Our research contributes to enhancing the safety and reliability of offshore structures by facilitating more precise assessments of stress distribution.Originality/valuePrecisely determining the SCF for the fatigue life of offshore structures reduces the potential hazards associated with fatigue failure, thereby guaranteeing their longevity and reliability. The present study offers a systematic approach for using FEA and ANN to calculate the stress distribution along the weld toe and the SCF in T-joints since ANNs are better at approximating complex phenomena than standard data fitting techniques. Once a database of parametric equations is available, it can be used to rapidly approximate the SCF, unlike experimentation, which is costly and FEA, which is time consuming.

Determination of stress concentration factors of welded joints from 3D-surface scans by artificial neural networks

The surface geometry and the stress concentration of welded joints show a large variation and are individual for each joint at each position. This is one reason for the conservative fatigue assessment of welded joints. In the past the determination of stress concentration factors (SCF) by Finite Element (FE) simulations was based on the approximated surface geometry of the weld, defined by weld toe radius and flank angle or other geometrical parameters. In this work a new approach is presented to directly determine SCFs of welded joints based on the 2D-profile (coordinates) of the weld surfaces. For this, two convolutional neural networks (CNN) PointNet++ and 2DLaserNet for point cloud classification are modified to perform regression on 2D-profiles. As input parameter artificial 2D-profiles were generated. The artificial neural networks (ANN) were trained by using the SCFs determined by Finite Element (FE)-simulations based on the virtual 2D-profiles. Both ANN show a high performance (R2 score) for the determination of SCFs. Comparison of the proposed method with three analytical solutions shows in two cases a higher agreement and in one case a similar agreement.

Determination of Stress Concentration Factor for a Stepped Bar Under Bending Loading: An Artificial Neural Networks Approach

Even today, charts and formulas derived from experimental determinations are used to obtain the stress concentration factor.Stress concentration factors from charts can be converted into numerical values using computational techniques. Stress concentration factor values were collected in a database and an Artificial Neural Network (ANN) model can be developed for improving the database. ANN model provides accuracy in obtaining the stress concentration factors. Using the static stress concentration factor for a stepped bar under a bending load we can quantify the impact of notches in fatigue.

Determination of Stress Concentration Factor for a Rectangular Bar with Fillet Under Axial Loading: An Artificial Neural Networks Approach

Using computer techniques, stress concentration factors from the graphs can be converted into numerical values. Stress concentration factor values were collected in a database and an Artificial Neural Network (ANN) model can be developed for improving and extending the database. ANN model provides accuracy in obtaining the stress concentration factor values.

Stress Concentration Factors of Concrete-Filled T-Joints under In-Plane Bending: Experiments, FE Analysis and Formulae.

Experimental and numerical investigations on seven cold-formed steel square hollow section (SHS) T-joints with concrete-filled chords were conducted for the determination of stress concentration factors (SCFs). The SCFs were experimentally determined using strain gauges and then numerically determined using Abaqus finite element analysis (FEA) software under static in-plane brace bending. Good agreement was observed between the two investigations. After validating the FEA results, a parametric study was conducted on the SCFs of concrete-filled SHS-SHS T-joints using Abaqus FEA to evaluate the effects of the non-dimensional parameters on the SCFs. Subsequently, design formulae for predicting the SCF of concrete-filled SHS-SHS T-joints subjected to in-plane bending were proposed. Comparable results were obtained between the numerical SCFs with SCFs calculated from the proposed design equations. The maximum SCF of concrete-filled SHS T-joints under in-plane brace bending occurred at different locations. The overall mean of the experimental reduction percentage in peak SCF due to concrete infill is 22% and the overall mean of the numerical reduction percentage in peak SCF due to concrete infill is 19%. The determination of SCFs in concrete-filled SHS-SHS T-joints under in-plane bending has been the subject of little research, and more information regarding the behavior of concrete-filled T-joints with SHS under in-plane bending needs to be provided to practicing engineers.

Statistical Characterization of Stress Concentrations along Butt Joint Weld Seams Using Deep Neural Networks

In order to ensure high weld qualities and structural integrity of engineering structures, it is crucial to detect areas of high stress concentrations along weld seams. Traditional inspection methods rely on visual inspection and manual weld geometry measurements. Recent advances in the field of automated measurement techniques allow virtually unrestricted numbers of inspections by laser measurements of weld profiles; however, in order to compare weld qualities of different welding processes and manufacturers, a deeper understanding of statistical distributions of stress concentrations along weld seams is required. Hence, this study presents an approach to statistically characterize different types of butt joint weld seams. For this purpose, an artificial neural network is created from 945 finite element simulations to determine stress concentration factors at butt joints. Besides higher quality of predictions compared to empirical estimation functions, the new approach can directly be applied to all types welded structures, including arc- and laser-welded butt joints, and coupled with all types of 3D-measurement devices. Furthermore, sheet thickness ranging from 1 mm to 100 mm can be assessed.

Experimental, numerical and parametric studies on stress concentration factors of T-joints under tension

This paper investigates the behaviour of square hollow section (SHS) T-joints under static axial tension for the determination of stress concentration factors (SCFs) at the hot spot locations. Five empty and corresponding concrete-filled SHS-SHS T-joint connections were tested experimentally and numerically. The experimental investigation was carried out by attaching strain gauges onto the SHS-SHS T-joint specimens. The numerical study was then conducted by developing three-dimensional finite element (FE) T-joint models using ABAQUS finite element analysis software for capturing the distribution of the SCFs at the hot spot locations. The results showed that there is a good agreement between the experimental and numerical SCFs. A series of formulae for the prediction of SCF in concrete-filled SHS T-joints under tension were proposed, and good agreement was achieved between the maximum SCFs in SHS T-joints calculated from FE T-joint models and those from the predicted formulae.

Circular hollow section X-connections near an open chord end: Stress concentration factors

This paper presents a numerical finite element (FE) investigation to determine stress concentration factors (SCFs) for circular hollow section (CHS)-to-CHS X-connections near an open chord end. Previous large-scale experiments are used to validate FE models, and a parametric study is performed. The parametric study consists of 240 models with variations in chord slenderness (2γ), branch-to-chord diameter ratio (β), branch-to-chord thickness ratio (τ), and chord end distance (e) on one side of the of the connection. For each of the 240 models, SCFs are determined at the crown and saddle hot-spot stress locations. Extrapolating existing formulae to predict “end-distance effects” on SCFs at these locations in CHS-to-CHS X-connections, from CIDECT Design Guide 8 (DG8), is shown to be inaccurate. Hence, SCF correction coefficients (ψ) and parametric formulae to estimate ψ (based on e/d0, 2γ and β) are derived.

Stress concentration factors for RHS-to-RHS X-connections near an open chord end

This paper presents an experimental and finite-element (FE) study to determine stress concentration factors (SCFs) for directly welded rectangular hollow section (RHS)-to-RHS axially loaded X-connections near an open chord end. Two-hundred and fifty-six FE models of RHS-to-RHS X-connections, with varied chord end distance-to-width (e/b0), branch-to-chord width (β), branch-to-chord thickness (τ), and chord slenderness (2γ) ratios were modelled and analyzed by using commercial software. The analysis was performed under quasi-static axial compression force(s) applied to the branch(es) and validated by comparison of strain concentration factors (SCNFs) to SCNFs obtained from two large-scale experimental tests. For all 256 connections, SCFs were determined at five critical hot spots on the side of the connection near the open chord end. The SCFs were found to vary as a function of e/b0, 2γ and β. Existing formulae in CIDECT DG8 to predict SCFs in directly welded RHS-to-RHS axially loaded X-connections are shown to be conservative when applied to a connection near an open chord end. SCF reduction factors (ψ), and a parametric formula to estimate ψ based on e/b0, 2γ and β, are derived.

Estimations of Stress Concentration Factors (Cw/Kts) For Helical Circular/Square Cross Sectional Tension-Compression Springs And Artificial Neural Network Modelling

Springs are used for various purposes in machine design as they can store energy under load, due to their elastic deformation characteristics. There are many types and profiles of springs. For a round wire helical compression or tension spring of small pitch angle, the Wahl factor, a correction factor (Cw) taking into account curvature and direct shear stress, is generally used in the design. The corresponding stress concentration factors, which may be useful for mechanics of materials problems, are obtained by taking the nominal shear stress τnom as the sum of the torsional stress (τ) and the direct shear stress (τ) for round wire. In the case of the wire of square cross-section, τnom is the sum of the torsional stress and the direct shear stress. For design calculations it is recommended that the simpler Wahl factor be used. The same value of max will be obtained whether one uses Cw or Kts. This study contains the determination of stress concentration factor and Wahl factor. For this aim, stress concentration factor charts were converted numerical values for round and square wires. These values were collected in an excel file. ANN (Artificial Neural Networks) model was developed using the data. It is an easy and convenient method, ANN model, was presented for the determination of stress concentration and Wahl factor for spring design.

Determination of stress concentration factor in the section of the composite plate weakened by the hole, upon contact of the hole with the cylinder

Problematic. When designing bolted joints (BJ), it is necessary, to carry out verification strength calculations. In this case, it is advisable to use express analysis: calculations using simple formulas of sufficient accuracy. One of the main strength calculations of BJ is the calculation of the gap section weakened by the hole. For BJ plates made of layered fibre-reinforced polymers (FRP), the problem has not yet been solved.Research objective. To verify the accuracy of two well-known express analysis formulas for stress concentration factors (SCF) at the contact of the hole with the bolt, using contrasting examples of materials and schemes for reinforcing FRP plates.Realization technique. Numerical calculations were carried out using the finite element method (contact problem) for a BJ plate made of layered FRP. A 3D orthotropy of each monolayer was assumed. Two simple express analysis formulas were tested. The results are tabulated. The illustrations are provided.The results of research. Numerical estimates are obtained that characterize the degree of influence of material characteristics and reinforcement patterns in a layered FRP plate and the accuracy of the formulas considered.Conclusions. A change in the material and the reinforcement scheme of the layered FRP leads to a significant change in the SCF values of the bolt-loaded hole in the section of the plate weakened by the hole, and the considered express analysis formulas have insufficient accuracy for contrast cases of materials and plate reinforcement schemes. More research is needed.

Determination of stress concentration factors for shafts under tension

Abstract Computer-based design and optimization have become increasingly important in recent years. This paper has investigated the stress concentration factors (SCF) Kt for shoulder filleted shafts with a hole and without a hole. This study contains two types of shoulder filleted shafts, i. e., a stepped bar of circular cross section with shoulder filleted and a tube with filleted shafts under tension stresses. Investigations on SCF that have been carried out in experimental and theoretical studies, were updated and validated for 2 types of shafts. The charts have been converted into numerical value using high precision computer techniques. Dimensional ratios and SCF were determined using previous work charts. This study determines maximum stresses for shoulder filleted shafts by three dimensional finite element analysis (FEA) and artificial intelligence techniques. A set of SCF charts was converted into numerical values and this data was organized and stored in an Excel file. ANSYS models were created and applied the boundary conditions on the models. And also mesh optimizations were performed. Artificial neural networks (ANN) models were designed using previously collected and verified data. Previous works, ANSYS and ANN results were compared to each other. As a result, ANN model and chart results show a good agreement. The usage of ANN model does not require any mathematical formulae or converting the numerical data action for determining the Kt result for shafts. ANN model usage was identified as a very useful and practical method.

An analytical approach to calculate stress concentration factors of machined surfaces

Machining operations affect the properties of the final surface layer, and these can impact on its functional performance, particularly on fatigue behaviour. Among the properties of the machined surface, surface topography is one major parameter affecting fatigue behaviour. The literature review has demonstrated that stress concentration factors Kt of the surface provide a more reliable estimation of the impact on the fatigue behaviour of machined components. Finite Element (FE) simulations can accurately calculate the stress concentration factor of machined surfaces, but they incur a high computational cost. Recent advances have shown that analytical models can reliably determine stress concentration factors of 2D roughness profiles. However, analytical models that predict stress concentration factors of 3D surface topographies are still lacking. This paper is aimed at developing an analytical method to calculate the stress concentration factor Kt of 3D surfaces generated by machining operations. To validate the model, a specimen of 7475-T7351 aluminium alloy was face milled and its surface topography was characterised using an Alicona IFG4 profilometer. Stress concentration factors were calculated in the selected surface regions using the proposed analytical model, and later compared to results obtained by FE simulations. The mean difference in the stress concentration factor Kt calculated by the proposed analytical and FE models is of 1.53%. Importantly, the developed analytical model reduces the computing time by 3000 times compared to FE models, and enables the analysis of larger surfaces.

Determination of stress concentration factors for shafts under tension

Abstract Computer-based design and optimization have become increasingly important in recent years. This paper has investigated the stress concentration factors (SCF) Kt for shoulder filleted shafts with a hole and without a hole. This study contains two types of shoulder filleted shafts, i. e., a stepped bar of circular cross section with shoulder filleted and a tube with filleted shafts under tension stresses. Investigations on SCF that have been carried out in experimental and theoretical studies, were updated and validated for 2 types of shafts. The charts have been converted into numerical value using high precision computer techniques. Dimensional ratios and SCF were determined using previous work charts. This study determines maximum stresses for shoulder filleted shafts by three dimensional finite element analysis (FEA) and artificial intelligence techniques. A set of SCF charts was converted into numerical values and this data was organized and stored in an Excel file. ANSYS models were created and applied the boundary conditions on the models. And also mesh optimizations were performed. Artificial neural networks (ANN) models were designed using previously collected and verified data. Previous works, ANSYS and ANN results were compared to each other. As a result, ANN model and chart results show a good agreement. The usage of ANN model does not require any mathematical formulae or converting the numerical data action for determining the Kt result for shafts. ANN model usage was identified as a very useful and practical method.

Stress concentration factors of RHS T-connections with galvanizing holes under in-plane bending

The hot spot stress method recommended by the CIDECT Design Guide 8 cannot be directly used in the fatigue design of galvanized tubular steel connections since: (1) the hot-dipping process can sometimes significantly change the residual stress magnitude and distribution at the welded joint; and (2) sufficiently large vent and drain holes must be specified at the welded joint location prior to galvanizing, and quite often at the locations recommended by the design guide for calculation of hot spot stresses. Hence, the existing formulae and charts for determination of Stress Concentration Factors (SCFs) may not be applicable. In this study, Finite Element (FE) modelling was performed to examine the existing SCF formulae for welded rectangular hollow section (RHS) T-connections under brace in-plane bending. The FE models were validated by comparison of the experimental results from six large-scale connection tests. A parametric study including 192 FE models with varied hole locations, brace-to-chord width ratios, chord wall slendernesses, and brace-to-chord thickness ratios, shows that the existing SCF formulae can lead to unsafe predictions. Critical hot spot stress locations are thus identified. The effects of both brace in-plane bending and chord loading were studied. New design formulae that take the vent and drain holes into account are proposed. These formulae are shown to provide more accurate predictions of SCFs in such connections.

Determination of stress concentration factor using applied element method

Determination of stress concentration factor using applied element method

Determination of stress concentration factors from photometric analysis data

The determination of stress concentration factors in local areas of metal structures plays an important role in the evaluation of structural strength. Existing computational methods for their evaluation take into account only the geometric characteristics of the stress concentrators, and the experimental methodologies are notable for their laboriousness and are unsuitable for use under operational conditions. The paper proposes a new method for evaluating the stress concentration factors and discusses the results of its use on the example of aluminium alloy with notches sample under fatigue test conditions.

Impact of notch geometry on dynamic strength of materials

Abstract The resilience of materials from the notch effect together with subsequent operating life and safety are important factors for the choice of material in industrial manufacture as well as for crash scenarios. The aim of this investigation is to study stress caused by the notch effect for HCT780XD and X5CrNi18-10 at different tensile test strain rates as well as due to various stress concentration factors during a high-speed tensile test. The notch geometries chosen are round, trapezoid, sharp and bore. They are compared to a test specimen without notch. The stress distribution analysis of notches was performed by the finite-element-method (FEM) in order to determine stress concentration factors. The high-speed tensile test was recorded with a high-speed camera. For this purpose, the test specimens were marked with a speckle-pattern, essential for the identification of strain rate via Dantec Dynamics Istra 4D. The influence of the stress concentration rate on parameters like energy, strength and the elongation of break was established and will be reported in the following. The level of the concentration factor leads to negative effects while the strain rate level delivers positive results. On other hand, the stress concentration factor is more important on the parameter than the strain rate. By contrast, Poisson's ratio does not affect the parameters observed.

Determination of stress concentration factors in offshore wind welded structures through a hybrid experimental and numerical approach

Offshore wind turbine (OWT) monopile support structures generally consist of steel cans connected together through circumferential welding joints. One critical factor to evaluate the localised increase in stresses is the stress concentration factor (SCF) which depends on the welding quality. The complex welding profiles in OWT monopiles makes the accurate calculation of SCF quite challenging. In this work, an innovative approach for the calculation of SCFs in offshore welded structures is proposed based on combined 3D (three-dimensional) laser scanning technology (LST) and 3D finite element analysis (FEA). The precise geometry of the welded specimens is captured using 3D LST, and then imported into a finite element software to perform 3D FEA modelling to accurately calculate SCFs. A 2D (two-dimensional) FEA model of a typical offshore welded structure with ideal geometry is also developed in this work. In addition to numerically calculate SCFs, the 2D FEA model is further combined with non-linear RSM (response surface method) to derive analytical equations, expressing SCFs of offshore welded structures in terms of key welding parameters. Both LST-FEA3D and RSM-FEA2D models are applied to calculate SCFs in large-scale S-N fatigue welded specimens. The results indicate that the LST-FEA3D approach is capable of capturing the variation of SCFs along the width of the welded specimens and identifying the critical points where fatigue crack is most likely to initiate; and the RSM-FEA2D is valuable and efficient in deriving analytical parametric equations for SCFs.

A Numerical Study of the Tensile Stress Concentration in a Hemi-ellipsoidal Corrosion Pit on a Plate

Fatigue cracks initiated from corrosion pits have been reported in various metallic structures under corrosive environments. Pit-to-crack transition occurs when the stress conditions around a corrosion pit exceed the endurance limit of the material. The effect of stress concentration at the site of a hemi-ellipsoidal corrosion pit on a metal plate was investigated using rigorous finite element analysis. Pit configuration and plate thickness were major parameters determining stress concentration factors (SCFs). Pit configuration and plate thickness were parameterized and the effects of each as a SCF were investigated. An increasing monotonic trend was evident as the pit became narrower and deeper. The effect of pit configuration was negligible, however, when the pit depth approached the plate thickness. Based on variations in the SCFs, parametric equations were developed via nonlinear regression analysis. The equations aptly represented each of the parameter characteristics and were used to accurately estimate their effect as a SCF.