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Eliasson, S., Hultgren, G., Barsoum, Z. & Wennhage, P. (2024). Probabilistic fatigue strength assessment of cross-ply laminates: Exploring effects of manufacturing defects through a two-scale modeling approach. Composite structures, 330, Article ID 117844.
Open this publication in new window or tab >>Probabilistic fatigue strength assessment of cross-ply laminates: Exploring effects of manufacturing defects through a two-scale modeling approach
2024 (English)In: Composite structures, ISSN 0263-8223, E-ISSN 1879-1085, Vol. 330, article id 117844Article in journal (Refereed) Published
Abstract [en]

The study presents a two-scale modeling approach allowing for an efficient fatigue strength evaluation on a macro scale considering a micro-mechanical defect characterization of a Carbon Fiber Reinforced Polymer (CFRP) material. The modeling approach integrates a macro model with the effective elastic properties from micro-mechanical simulations considering voids. This enables the analysis of defects’ influence on material fatigue strength using a probabilistic weakest link approach. A CFRP laminate with a cross-ply layup was investigated. Two simulation case studies demonstrate the effect of void content and size on the characteristic fatigue strength. An experimental investigation was conducted testing the laminates in tension–tension fatigue verifying the predicted numerical behavior. The numerical models identify a difference in the characteristic fatigue strength consistent with the fatigue test results. It is numerically concluded that the investigated CFRP material's fatigue strength is affected by the presence of voids and even with only a slight difference in the global void volume fraction a scatter in fatigue strength is identified.

Place, publisher, year, edition, pages
Elsevier BV, 2024
Keywords
Carbon fiber, Fatigue, Finite element analysis, Multi-scale modeling, Porosity
National Category
Composite Science and Engineering Applied Mechanics
Identifiers
urn:nbn:se:kth:diva-342179 (URN)10.1016/j.compstruct.2023.117844 (DOI)2-s2.0-85181172124 (Scopus ID)
Note

QC 20240115

Available from: 2024-01-15 Created: 2024-01-15 Last updated: 2024-01-15Bibliographically approved
Alhourani, A., Sheikh-Ahmad, J., Almaskari, F., Khan, K., Deveci, S. & Barsoum, Z. (2024). Thermal modeling of friction stir welding of thick high-density polyethylene plates. Journal of Materials Research and Technology, 28, 4186-4198
Open this publication in new window or tab >>Thermal modeling of friction stir welding of thick high-density polyethylene plates
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2024 (English)In: Journal of Materials Research and Technology, ISSN 2238-7854, Vol. 28, p. 4186-4198Article in journal (Refereed) Published
Abstract [en]

The process temperatures in the friction stir welding of thick polymer plates play a significant role in the joint's quality since the process is characterized by mixed solid and viscous flow states. The heat generation mechanism in each state is fundamentally different, with heat being generated by friction in the solid-state and by viscous shear flow in the viscous state. In this study, the heat generation and dissipation in the friction stir welding of 14 mm thick high-density polyethylene plates were studied numerically through solving the direct heat conduction problem. Two models of heat generation were used in the numerical solution and the effect of the pin rotational speed on the process temperatures was investigated. It was shown that the utilization of a mixed heat generation model consisting of both the solid state and the viscous shear flow considerably improves the numerical model predictions. The temperature predictions were validated through welding experiments and showed a temperature difference of 3 %. Furthermore, it was found that the welding process stabilizes at rotational speeds higher than 800 rpm, where no considerable change occurs in the volume of the viscous flow region and the welding power requirement. The numerical results based on the combined solid-viscous heat model were in good agreement with the experimental thermal histories.

Place, publisher, year, edition, pages
Elsevier BV, 2024
Keywords
Friction stir welding, Numerical thermal model, Thick high-density polyethylene, Viscous heat generation, Welding temperatures
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-343189 (URN)10.1016/j.jmrt.2024.01.044 (DOI)001158275400001 ()2-s2.0-85183594193 (Scopus ID)
Note

QC 20240209

Available from: 2024-02-08 Created: 2024-02-08 Last updated: 2024-02-26Bibliographically approved
Hultgren, G., Mansour, R. & Barsoum, Z. (2023). Fatigue strength assessment of welded joints incorporating the variability in local weld geometry using a probabilistic framework. International Journal of Fatigue, 167, Article ID 107364.
Open this publication in new window or tab >>Fatigue strength assessment of welded joints incorporating the variability in local weld geometry using a probabilistic framework
2023 (English)In: International Journal of Fatigue, ISSN 0142-1123, E-ISSN 1879-3452, Vol. 167, article id 107364Article in journal (Refereed) Published
Abstract [en]

Progress in developing digital quality assurance systems for welded joints has made it possible to accurately measure the local geometry and its variation, making it possible to derive new relations between the geometric variations and fatigue. A probabilistic model for the fatigue strength is here presented based on the actual weld geometry. The novelty lies in that representative stresses can be determined for both the complete weld and sections of the weld. Calibration of the model using 105 fatigue-tested specimens shows a reduced variation in SN-diagrams compared with the nominal stress methods when substantial weld geometry variations are present.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Probabilistic analysis, Fatigue strength, Welded joints, Weld geometry
National Category
Manufacturing, Surface and Joining Technology
Identifiers
urn:nbn:se:kth:diva-322875 (URN)10.1016/j.ijfatigue.2022.107364 (DOI)000892572600001 ()2-s2.0-85141921127 (Scopus ID)
Note

QC 20230109

Available from: 2023-01-09 Created: 2023-01-09 Last updated: 2024-01-16Bibliographically approved
Hultgren, G., Boåsen, M., Narström, T. & Barsoum, Z. (2023). Fracture toughness assessment of surface cracks in slender ultra-high-strength steel plates. Engineering Fracture Mechanics, 289, Article ID 109458.
Open this publication in new window or tab >>Fracture toughness assessment of surface cracks in slender ultra-high-strength steel plates
2023 (English)In: Engineering Fracture Mechanics, ISSN 0013-7944, E-ISSN 1873-7315, Vol. 289, article id 109458Article in journal (Refereed) Published
Abstract [en]

Safe design against unstable fractures in load-bearing structures is crucial at sub-zero temperatures where the brittle fracture toughness can be unfavourable, especially for high-stress designs incorporating ultra-high-strength steels. The brittle fracture toughness of surface cracks in structural steel with a minimum yield strength of 1300 MPa is, for this reason, tested in the present study at sub-zero temperatures. The realistic flaws are compared with single-edge notched specimens (SEN(B)) from thicker plates with the same chemical composition, using a representative fracture toughness for a three-dimensional crack front according to the Master Curve method. A novel approach determines the latter without considering the local temperature and constraint variation through empirical relations. The experimental result shows a difference in the reference temperature between the two specimen types, which likely is the natural variation of the manufactured materials and/or a loss of constraint due to the difference in the scaled specimen deformation level.

Place, publisher, year, edition, pages
Elsevier Ltd, 2023
Keywords
Brittle fracture, Fracture toughness, Master Curve method, Surface flaw
National Category
Applied Mechanics
Identifiers
urn:nbn:se:kth:diva-334356 (URN)10.1016/j.engfracmech.2023.109458 (DOI)001045219200001 ()2-s2.0-85164677385 (Scopus ID)
Note

QC 20230821

Available from: 2023-08-21 Created: 2023-08-21 Last updated: 2024-01-16Bibliographically approved
Lundkvist, A., Barsoum, I., Barsoum, Z. & Khurshid, M. (2023). Geometric and Material Modelling Aspects for Strength Prediction of Riveted Joints. Metals, 13(3), 500, Article ID 500.
Open this publication in new window or tab >>Geometric and Material Modelling Aspects for Strength Prediction of Riveted Joints
2023 (English)In: Metals, ISSN 2075-4701, Vol. 13, no 3, p. 500-, article id 500Article in journal (Refereed) Published
Abstract [en]

The aim of this study is to develop a methodology for static strength and failure mode simulation of hot-driven riveted joints. The purpose is to be able to accurately estimate a rivet joint's static strength behaviour and its failure mode without relying on experiments, to save both time and resources during the design of joints. The non-linear finite element analysis modelling framework considered the rivet joint configurations and geometry, the material properties of the plate and rivet as well as the clamping force of the hot-driven rivet. A ductile damage model was also implemented to capture the stress softening of the materials and the failure modes of the joints. Using experimental data from literature, the modelling framework is validated, and it is shown that it is able to capture the strength behaviour and failure modes of different configurations of rivet joints markedly well. The effect of the rivet pre-load on the mechanical response of the joint is also studied and it is shown that the strength of the joint increased with the increase in rivet pre-load. The modelling framework is then applied to an industrial component. The modelling framework is used to compare welding and riveting as joining methods in a component built in two grades of high-strength steel. It is found that the welded joint possessed greater strength compared to the proposed riveted joint. However, using the proposed simulation methodology developed, a riveted joint with matching strength to the welded joint could be designed.

Place, publisher, year, edition, pages
MDPI AG, 2023
Keywords
rivet joints, hot-driven solid rivets, finite element analysis, ultimate strength, failure analysis
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:kth:diva-326582 (URN)10.3390/met13030500 (DOI)000968347500001 ()2-s2.0-85152667013 (Scopus ID)
Note

QC 20230508

Available from: 2023-05-08 Created: 2023-05-08 Last updated: 2024-03-15Bibliographically approved
Eliasson, S., Hagnell, M. K., Wennhage, P. & Barsoum, Z. (2022). A Statistical Porosity Characterization Approach of Carbon-Fiber-Reinforced Polymer Material Using Optical Microscopy and Neural Network. Materials, 15(19), Article ID 6540.
Open this publication in new window or tab >>A Statistical Porosity Characterization Approach of Carbon-Fiber-Reinforced Polymer Material Using Optical Microscopy and Neural Network
2022 (English)In: Materials, ISSN 1996-1944, E-ISSN 1996-1944, Vol. 15, no 19, article id 6540Article in journal (Refereed) Published
Abstract [en]

The intensified pursuit for lightweight solutions in the commercial vehicle industry increases the demand for method development of more advanced lightweight materials such as Carbon-Fiber-Reinforced Composites (CFRP). The behavior of these anisotropic materials is challenging to understand and manufacturing defects could dramatically change the mechanical properties. Voids are one of the most common manufacturing defects; they can affect mechanical properties and work as initiation sites for damage. It is essential to know the micromechanical composition of the material to understand the material behavior. Void characterization is commonly conducted using optical microscopy, which is a reliable technique. In the current study, an approach based on optical microscopy, statistically characterizing a CFRP laminate with regard to porosity, is proposed. A neural network is implemented to efficiently segment micrographs and label the constituents: void, matrix, and fiber. A neural network minimizes the manual labor automating the process and shows great potential to be implemented in repetitive tasks in a design process to save time. The constituent fractions are determined and they show that constituent characterization can be performed with high accuracy for a very low number of training images. The extracted data are statistically analyzed. If significant differences are found, they can reveal and explain differences in the material behavior. The global and local void fraction show significant differences for the material used in this study and are good candidates to explain differences in material behavior.

Place, publisher, year, edition, pages
MDPI AG, 2022
Keywords
Carbon-Fiber-Reinforced Polymer, porosity, Convolutional Neural Network, optical microscopy
National Category
Composite Science and Engineering
Identifiers
urn:nbn:se:kth:diva-320659 (URN)10.3390/ma15196540 (DOI)000867957800001 ()36233894 (PubMedID)2-s2.0-85139979487 (Scopus ID)
Note

QC 20221101

Available from: 2022-11-01 Created: 2022-11-01 Last updated: 2024-03-18Bibliographically approved
Eliasson, S., Karlsson Hagnell, M., Wennhage, P. & Barsoum, Z. (2022). An Experimentally Based Micromechanical Framework Exploring Effects of Void Shape on Macromechanical Properties. Materials, 15(12), 4361, Article ID 4361.
Open this publication in new window or tab >>An Experimentally Based Micromechanical Framework Exploring Effects of Void Shape on Macromechanical Properties
2022 (English)In: Materials, ISSN 1996-1944, E-ISSN 1996-1944, Vol. 15, no 12, p. 4361-, article id 4361Article in journal (Refereed) Published
Abstract [en]

A micromechanical simulation approach in a Multi-Scale Modeling (MSM) framework with the ability to consider manufacturing defects is proposed. The study includes a case study where the framework is implemented exploring a cross-ply laminate. The proposed framework highlights the importance of correct input regarding micromechanical geometry and void characteristics. A Representative Volume Element (RVE) model is developed utilizing true micromechanical geometry extracted from micrographs. Voids, based on statistical experimental data, are implemented in the RVE model, and the effects on the fiber distribution and effective macromechanical properties are evaluated. The RVE algorithm is robust and maintains a good surrounding fiber distribution around the implemented void. The local void fraction, void size, and void shape affect the effective micromechanical properties, and it is important to consider the phenomena of the effective mechanical properties with regard to the overall void fraction of an RVE and the actual laminate. The proposed framework has a good prediction of the macromechanical properties and shows great potential to be used in an industrial implementation. For an industrial implementation, weak spots and critical areas for a laminate on a macro-level are found through combining local RVEs.

Place, publisher, year, edition, pages
MDPI AG, 2022
Keywords
CFRP, porosity, multi-scale modeling, representative volume elements, microstructure
National Category
Materials Engineering
Identifiers
urn:nbn:se:kth:diva-315513 (URN)10.3390/ma15124361 (DOI)000817472200001 ()35744416 (PubMedID)2-s2.0-85132859954 (Scopus ID)
Note

QC 20220707

Available from: 2022-07-07 Created: 2022-07-07 Last updated: 2023-11-08Bibliographically approved
Tyystjärvi, T., Virkkunen, I., Fridolf, P., Rosell, A. & Barsoum, Z. (2022). Automated defect detection in digital radiography of aerospace welds using deep learning. Welding in the World, 66(4), 643-671
Open this publication in new window or tab >>Automated defect detection in digital radiography of aerospace welds using deep learning
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2022 (English)In: Welding in the World, ISSN 0043-2288, E-ISSN 1878-6669, Vol. 66, no 4, p. 643-671Article in journal (Refereed) Published
Abstract [en]

Aerospace welds are non-destructively evaluated (NDE) during manufacturing to identify defective parts that may pose structural risks, often using digital radiography. The analysis of these digital radiographs is time consuming and costly. Attempts to automate the analysis using conventional computer vision methods or shallow machine learning have not, thus far, provided performance equivalent to human inspectors due to the high reliability requirements and low contrast to noise ratio of the defects. Modern approaches based on deep learning have made considerable progress towards reliable automated analysis. However, limited data sets render current machine learning solutions insufficient for industrial use. Moreover, industrial acceptance would require performance demonstration using standard metrics in non-destructive evaluation, such as probability of detection (POD), which are not commonly used in previous studies. In this study, data augmentation with virtual flaws was used to overcome data scarcity, and compared with conventional data augmentation. A semantic segmentation network was trained to find defects from computed radiography data of aerospace welds. Standard evaluation metrics in non-destructive testing were adopted for the comparison. Finally, the network was deployed as an inspector’s aid in a realistic environment to predict flaws from production radiographs. The network achieved high detection reliability and defect sizing performance, and an acceptable false call rate. Virtual flaw augmentation was found to significantly improve performance, especially for limited data set sizes, and for underrepresented flaw types even at large data sets. The deployed prototype was found to be easy to use indicating readiness for industry adoption. 

Place, publisher, year, edition, pages
Springer Nature, 2022
Keywords
Data augmentation, Deep learning, Non-destructive evaluation, Probability of detection, Welding, Defects, E-learning, Image segmentation, Semantics, Welds, Automated defect detection, Conventional computers, Defective parts, Digital radiography, Limited data sets, Non destructive evaluation, Structural risks, Nondestructive examination
National Category
Computer Sciences Medical Image Processing
Identifiers
urn:nbn:se:kth:diva-321189 (URN)10.1007/s40194-022-01257-w (DOI)000761829500001 ()2-s2.0-85125150233 (Scopus ID)
Note

QC 20221109

Available from: 2022-11-09 Created: 2022-11-09 Last updated: 2022-11-09Bibliographically approved
Cheemakurthy, H., Barsoum, Z., Burman, M. & Garme, K. (2022). Comparison of Lightweight Structures in Bearing Impact Loads during Ice–Hull Interaction. Journal of Marine Science and Engineering, 10(6), 794, Article ID 794.
Open this publication in new window or tab >>Comparison of Lightweight Structures in Bearing Impact Loads during Ice–Hull Interaction
2022 (English)In: Journal of Marine Science and Engineering, E-ISSN 2077-1312, Vol. 10, no 6, p. 794-, article id 794Article in journal (Refereed) Published
Abstract [en]

The current study focuses on the impact loading phase characteristic of thin first year ice in inland waterways. We investigate metal grillages, fibre reinforced plastic (FRP) composites and nature-inspired composites using LS Dyna. The impact mode is modelled as (a) simplified impact model with a rigid-body impactor and (b) an experimentally validated ice model represented by cohesive zone elements. The structural concepts are investigated parametrically for strength and stiffness using the simplified model, and an aluminium alloy grillage is analysed with the ice model. The metal–FRP composite was found to be the most favourable concept that offered impact protection as well as being light weight. By weight, FRP composites with a Bouligand ply arrangement were the most favourable but prone to impact damage. Further, aluminium grillage was found to be a significant contender for a range of ice impact velocities. While the ice model is experimentally validated, a drawback of the simplified model is the lack of experimental data. We overcame this by limiting the scope to low velocity impact and investigating only relative structural performance. By doing so, the study identifies significant parameters and parametric trends along with material differences for all structural concepts. The outcomes result in the creation of a viable pool of lightweight variants that fulfil the impact loading phase. Together with outcomes from quasi-static loading phase, it is possible to develop a lightweight ice-going hull concept.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI AG, 2022
Keywords
composites; metal grillage; aluminium hull; ice loads; LS Dyna; urban waterborne mobility; inland waterways; impact modelling; bio-inspired structures; ice-going hull
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-313910 (URN)10.3390/jmse10060794 (DOI)000817667100001 ()2-s2.0-85132789739 (Scopus ID)
Projects
Lightweight ice going hull structures.
Funder
Swedish Transport Administration, TRV 2018/6471
Note

QC 20220613

Available from: 2022-06-13 Created: 2022-06-13 Last updated: 2023-03-22Bibliographically approved
Zhu, J., Barsoum, I., Barsoum, Z. & Khurshid, M. (2022). Evaluation of local stress-based fatigue strength assessment methods for cover plates and T-joints subjected to axial and bending loading. Fatigue & Fracture of Engineering Materials & Structures, 45(9), 2531-2548
Open this publication in new window or tab >>Evaluation of local stress-based fatigue strength assessment methods for cover plates and T-joints subjected to axial and bending loading
2022 (English)In: Fatigue & Fracture of Engineering Materials & Structures, ISSN 8756-758X, E-ISSN 1460-2695, Vol. 45, no 9, p. 2531-2548Article in journal (Refereed) Published
Abstract [en]

This study aims to find suitable fatigue assessment methods for welded structures (cover plates and T-joints) subjected to axial and bending loading. The Hot Spot Stress (HSS), 1-mm stress (OM), Theory of Critical Distances (TCD), Stress Averaging (SA), and Effective Notch Stress (ENS) methods are evaluated in terms of accuracy and reliability. The evaluation is based on fatigue test data extracted from the literature and carried out in this study. It is found that the SA method can be used to assess the fatigue strength of cover plate joints under axial loading with relatively good accuracy and low scatter, followed by the ENS method. The HSS, TCD, SA, and ENS methods are conservative estimation methods for T-joints under bending, while the accuracy is low. Furthermore, fatigue design curves applicable for T-joints under bending are discussed, which can be used in the TCD method and SA method.

Place, publisher, year, edition, pages
Wiley, 2022
Keywords
effective notch stress, fatigue strength assessment, hot spot stress, 1-mm stress, Stress averaging, Theory of Critical Distances, weld toe failure
National Category
Building Technologies
Identifiers
urn:nbn:se:kth:diva-319452 (URN)10.1111/ffe.13764 (DOI)000811370900001 ()2-s2.0-85131892969 (Scopus ID)
Note

QC 20230920

Available from: 2022-10-03 Created: 2022-10-03 Last updated: 2024-03-15Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4180-4710

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