| 1. |
- Delkhosh, Ehsan, et al.
(författare)
-
Fracture mechanics and fatigue life assessment of box-shaped welded structures : FEM analysis and parametric design
- 2020
-
Ingår i: Welding in the World. - : Springer. - 0043-2288 .- 1878-6669. ; 64:9, s. 1535-1551
-
Tidskriftsartikel (refereegranskat)abstract
- In this study, Linear Elastic Fracture Mechanics (LEFM) approach is used to evaluate the fatigue strength of a box-shaped welded structure. A parametric study is also undertaken to study the effect of various weld parameters on the fatigue strength, such as lack of weld metal penetration, load position, and plate thicknesses. FRANC3D software was adopted to obtain the stress intensity factor values for two types of full-length and intermediate crack sizes, located at the critical region of the weld of the box-shaped structure. It was concluded that the LEFM approach could capture the crack propagation from the weld root reasonably well under the given conditions and estimate residual fatigue life of the welded structures conservatively. Compared to fatigue life estimations by nominal stress method (1,714,564 cycles) or effective notch stress method (63,385 cycles), the LEFM approach can estimate the residual life more accurately. Especially for intermediate (4 mm) lack of penetration (LOP) of weld metal case (589,198 cycles) in comparison to the experiments (1,216,595 cycles). The parametric study showed that the fatigue life increases with increase in the thickness of flanges, lesser LOP in the weld root, and when load is applied more toward the center of the plate.
|
|
| 2. |
- Almomani, Abdulla, et al.
(författare)
-
Constitutive model calibration for the thermal viscoelastic-viscoplastic behavior of high density polyethylene under monotonic and cyclic loading
- 2023
-
Ingår i: Polymer testing. - : Elsevier BV. - 0142-9418 .- 1873-2348. ; 118
-
Tidskriftsartikel (refereegranskat)abstract
- High density polyethylene (HDPE) can show viscoelastic-viscoplastic behaviors under monotonic loads and a stress softening after reloading under cyclic ones. This sets a challenge in simultaneously representing such response in material constitutive models. In addition, due to the adoption of novel accelerated tests at higher temperatures, e.g., 95 degrees C, the need for a higher temperature calibration is motivated. Therefore, the objective of this study is threefold: (i) to investigate the capability of the three network viscoplastic (TNV) model in capturing HDPE thermo-viscoplasticity under monotonic and cyclic loads, (ii) to report observations on HDPE at various strain-rates and temperatures from 23 degrees C to 95 degrees C including the alpha-relaxation region (iii) to explore the ratcheting behavior of HDPE, i.e., cyclic creep. The FEA analysis based on the calibrated TNV model was successfully able to predict the HDPE behavior under static, quasi-static and dynamic loads. The predicted strain range Delta epsilon and midrange strain epsilon s of the cyclic creep showed good agreements. This implies that the TNV model can be a reliable candidate for HDPE engineering assessments. Findings of this work will have many industrial applications, e.g., products manufacturers or resin producers, in which HDPE is used under complex loads. Similar procedures can be followed for other thermoplastics which lays the basis for establishing a standard calibration guideline.
|
|
| 3. |
- Altamimi, S., et al.
(författare)
-
On Stiffness, Strength, Anisotropy, and Buckling of 30 Strut-Based Lattices with Cubic Crystal Structures
- 2022
-
Ingår i: Advanced Engineering Materials. - : Wiley. - 1438-1656 .- 1527-2648. ; 24:7
-
Tidskriftsartikel (refereegranskat)abstract
- Architected cellular structures are increasingly receiving attention in numerous applications due to advances in additive manufacturing and their promising multi-functional properties. Herein, 30 architected strut-based lattices of cubic crystal symmetry are developed and their stiffness and strength are investigated computationally and experimentally. Finite element simulations are conducted to compute the effective stiffness, yield strength, and buckling strength under uniaxial, shear, and hydrostatic loadings. Also, elastic anisotropy is assessed and bifurcation analysis is performed to estimate the threshold relative density for each lattice. Selected lattices of various relative densities are 3D printed from a polymeric material using selective laser sintering (SLS). The numerical results show that the modes of deformation whether stretching-dominated, bending-dominated, or mixed differ for the various loading conditions. It is observed that by combining different lattice structures in a hybrid approach, a decrease in the anisotropic behavior is obtained, and an overall enhancement of the mechanical properties is achieved. The numerical results show rather good agreement with the experimental findings. The current study can be crucial for using the investigated lattices for enhancing the multi-functional properties of structural systems.
|
|
| 4. |
- Mourad, Abdel Hamid, I, et al.
(författare)
-
Impact Strengthening of Laminated Kevlar/Epoxy Composites by Nanoparticle Reinforcement
- 2020
-
Ingår i: Polymers. - : MDPI. - 2073-4360. ; 12:12
-
Tidskriftsartikel (refereegranskat)abstract
- Herein, we report the fabrication and characterization of high-strength Kevlar epoxy composite sheets for structural application. This process includes optimization of the curing conditions of composite preparation, such as curing time and temperature, and the incorporation of nanofillers, such as aluminum oxide (Al2O3), silicon carbide (SiC), and multi-walled carbon nanotubes (MWCNT) in different weight percentages. Differential scanning calorimetry (DSC) was utilized to investigate the thermal stability and curing behavior of the epoxy, finding that a minimum of 5 min is required for complete curing under an optimized temperature of 170 degrees C. Moreover, mechanical characterization, including flexural and drop-weight tests, were performed and found to be in good agreement with the DSC results. Our results show that nanofiller incorporation improves the mechanical properties of Kevlar epoxy composites. Among the tested samples, 0.5% MWCNT incorporation obtained the highest mechanical strength.
|
|
| 5. |
- Negi, Alok, et al.
(författare)
-
A gradient-enhanced damage model for anisotropic brittle fracture with interfacial damage in polycrystalline materials
- 2023
-
Ingår i: Engineering Fracture Mechanics. - : Elsevier BV. - 0013-7944 .- 1873-7315. ; 280
-
Tidskriftsartikel (refereegranskat)abstract
- This article presents a nonlocal gradient-enhanced damage model that uses direction-dependent damage evolution and interfacial damage to predict transgranular and intergranular cracks in polycrystalline materials at the microstructural level. The distinct grains within the polycrystalline morphology are modeled as anisotropic linear elastic domains with random spatial orientation and cubic symmetries. Transgranular micro-cracks are assumed to occur along specific preferential cleavage planes within each randomly oriented crystal and are described using a bulk damage variable. For intergranular fracture, a smeared description of interface decohesion is incorporated through an interface damage variable which depends on the modified interface kinematics based on a cohesive law that uses a smoothed displacement jump approximation. The coupled system of equations in the proposed computational framework is decoupled using an operator-split methodology to ensure a robust and straightforward computational implementation. Several numerical examples are presented, and simulations are performed on single crystal, bicrystals, and polycrystalline domains to demonstrate the capabilities and validation of the proposed model.
|
|
| 6. |
|
|
| 7. |
- Tyystjärvi, T., et al.
(författare)
-
Automated defect detection in digital radiography of aerospace welds using deep learning
- 2022
-
Ingår i: Welding in the World. - : Springer Nature. - 0043-2288 .- 1878-6669. ; 66:4, s. 643-671
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
