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23 pages, 9093 KiB  
Article
Mechanical and Metallurgical Characterization of Advance High Strength Steel Q&P1180 Produced by Two Different Suppliers
by Michele Maria Tedesco, Pietro Licignano, Antonio Mara, Stefano Plano, Davide Gabellone, Matteo Basso and Marcello Baricco
Metals 2025, 15(3), 301; https://doi.org/10.3390/met15030301 - 10 Mar 2025
Viewed by 166
Abstract
Through mechanical analysis, a comparison of the same type of cold rolled steel produced by two steel manufacturers, supplier 1 and supplier 2, has been carried out. The considered material is a steel that has undergone a quenching and partitioning heat treatment, i.e., [...] Read more.
Through mechanical analysis, a comparison of the same type of cold rolled steel produced by two steel manufacturers, supplier 1 and supplier 2, has been carried out. The considered material is a steel that has undergone a quenching and partitioning heat treatment, i.e., a rapid cooling from the austenitizing temperature, followed by a holding treatment at a suitable temperature, so that the residual austenite is stabilized at room temperature. The following tests for mechanical properties were carried out: formability, through Nakajima test, tensile test, bending test, hole expansion test and fatigue strength analysis, through high cycle fatigue and low cycle fatigue test. In addition, to derive useful data for future simulations, tensile and Nakajima tests were analyzed by digital image correlation, which uses a monochrome camera to capture frames during the test, in order to analyze local deformations on investigated samples. Finite elements modeling has been carried out. A suitable calibration of a material card for the Abaqus Finite Element Analysis software has been performed. Through the combination of obtained results, a rational comparison of the two analyzed products has been obtained. Full article
(This article belongs to the Special Issue Design, Processing and Characterization of Metals and Alloys)
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Figure 1

Figure 1
<p>Q&amp;P thermal process. ANN: Annealing Temperature; QT: Quenching Temperature; PT: Partitioning Temperature; M<sub>S</sub>: Martensite start temperature; M<sub>F</sub>: Martensite finish temperature; <span class="html-italic">Ci</span>, <span class="html-italic">Cγ</span>, and <span class="html-italic">C<sub>m</sub></span> are the carbon contents in the initial alloy, austenite, and martensite, respectively. Reprinted from Ref. [<a href="#B10-metals-15-00301" class="html-bibr">10</a>].</p>
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<p>Samples used in the formability test.</p>
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<p>Sample geometries: (<b>a</b>) dog bone, (<b>b</b>) notch and (<b>c</b>) shear; all dimensions are in mm.</p>
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<p>Samples recreated for simulation and their boundary conditions: (<b>a</b>) dog bone sample, (<b>b</b>) notch sample, and (<b>c</b>) shear sample. Δ is the clamped side, and D is the direction of the tensile force.</p>
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<p>Graphic depiction of the progressive damage method. (a) starting point of tensile test, (b) end of elastic behavior, (c) starting point of plastic behavior, (d) damage starts, (e) complete failure of sample, (e′) end of test in ipotetical true curve without damage condition.</p>
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<p>Micrography of Q&amp;P1180 obtained from (<b>a</b>) supplier 1 and (<b>b</b>) supplier 2. The top images are at 500× magnification, those below at 1000× magnification. RA represents the retained austenite.</p>
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<p>Formability limit curves for Q&amp;P1180 steels obtained from supplier 1 and supplier 2. Results obtained for a conventional Dual Phase 980 steel grade are reported for comparison.</p>
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<p>Woehler’s curve in HCF for Q&amp;P1180 steel obtained from supplier 1.</p>
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<p>Woehler’s curve in HCF for Q&amp;P1180 steel obtained from supplier 2.</p>
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<p>Morrow’s curve in LCF for Q&amp;P1180 steel obtained from supplier 1.</p>
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<p>Morrow’s curve in LCF for Q&amp;P1180 steel obtained from supplier 2.</p>
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<p>Tensile test of samples obtained from different suppliers measured along the longitudinal direction with respect to the rolling one.</p>
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<p>Tensile test of samples obtained from different suppliers measured along the diagonal direction with respect to the rolling one.</p>
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<p>Tensile test of samples obtained from different suppliers measured along the transversal direction with respect to the rolling one.</p>
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<p>Comparison between simulated (green) and experimental (purple) tensile test curve of a dog-bone sample.</p>
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<p>Logarithmic strain component (<b>a</b>) and real dog-bone sample maximum deformation (<b>b</b>).</p>
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<p>Comparison of simulated (green) and real (purple) curve of a notch sample.</p>
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<p>Logarithmic strain component (<b>a</b>) and real notch sample maximum deformation (<b>b</b>).</p>
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<p>Comparison of simulated (green) and real (purple) curve of shear sample.</p>
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<p>Logarithmic strain component (<b>a</b>) and real shear sample maximum deformation (<b>b</b>).</p>
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18 pages, 4742 KiB  
Article
Research on Modeling for the Flow–Compaction Process of Thermosetting Epoxy Resin-Based Composites
by Ye Jing, Zhenyi Yuan, Kai He, Lingfei Kong, Guigeng Yang and Kaite Guo
Polymers 2025, 17(6), 722; https://doi.org/10.3390/polym17060722 - 10 Mar 2025
Viewed by 81
Abstract
Addressing the issue of porosity evolution during the curing process of thermosetting epoxy resin-based composites, a simulation model has been developed to describe the flow–compaction behavior of the composites aiming to predict changes in porosity throughout the curing process. Initially, a multi-physics coupling [...] Read more.
Addressing the issue of porosity evolution during the curing process of thermosetting epoxy resin-based composites, a simulation model has been developed to describe the flow–compaction behavior of the composites aiming to predict changes in porosity throughout the curing process. Initially, a multi-physics coupling model encompassing sub-models for thermo-chemical, fiber bed compression, void compression, and percolation flow was established. This model accurately describes the changes in porosity within the composites during the flow–compaction process. The UMAT subroutine of the ABAQUS finite element analysis software was utilized to integrate these sub-models into the software. The validity of the simulation model was verified through corresponding experimental porosity measurements. The research further indicates that the porosity at the fillet of L-shaped composite components is higher than that in flat areas due to insufficient shear slip capacity. The results show that the porosity of the rounded corners of the L-shaped composite members is higher than that of the flat plate region due to the lack of shear slip capacity, and the fiber bed stiffness and inter-ply friction coefficient play an important role in the change in porosity. Full article
(This article belongs to the Special Issue Polymer Manufacturing Processes)
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Graphical abstract

Graphical abstract
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<p>Diagram of void compression during flow–compaction process.</p>
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<p>The flowchart of flow–compaction model.</p>
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<p>Preparation of L-shaped composite material parts. (<b>a</b>) Dimensions of L-shaped composite material parts; (<b>b</b>) cured L-shaped composite material parts.</p>
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<p>CT scanner and model reconstruction of composite l-shaped parts. (<b>a</b>) Nano Voxel computed tomography (CT) scanner; (<b>b</b>) the reconstructed model based on CT scan three-dimensional data.</p>
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<p>Schematic diagram for cutting [0/45/−45/90]<sub>2s</sub> laminate composite material parts.</p>
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<p>Scanning results of void content in [0/45/−45/90]<sub>2s</sub> composite material component (red represents voids, and white represents areas without voids). (<b>a</b>) Before curing; (<b>b</b>) after curing.</p>
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<p>Applied boundary conditions of the FE model.</p>
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<p>The simulation results of temperature and DoC at the surface and center point of the composite part.</p>
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<p>Updated porosity content distribution for three different laminates (SDV 10 represents the porosity of the composite). (<b>a</b>) The [0]<sub>12</sub> layup; (<b>b</b>) [0]<sub>16</sub> layup; (<b>c</b>) [0/45/−45/90]<sub>2s</sub> layup.</p>
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<p>The effect of compaction curve scaling parameter on the final porosity of composite.</p>
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<p>Nesting phenomenon during fiber compression.</p>
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<p>The effect of inter-ply friction on the final porosity of composite.</p>
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<p>The effect of void distance on the final porosity of composite.</p>
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21 pages, 12263 KiB  
Article
Flexural Behavior of Wet Joints with Contact U-Bars
by Yuancong Wu, Songtao Hu, Meng Li and Bin Rong
Buildings 2025, 15(6), 855; https://doi.org/10.3390/buildings15060855 - 10 Mar 2025
Viewed by 147
Abstract
In this study, seven wet joint specimens of contact U-bars are designed in order to evaluate the flexural behavior of the wet joints in precast concrete slabs through four-point bending tests. This study investigates the effects of lap length, wet joint width, and [...] Read more.
In this study, seven wet joint specimens of contact U-bars are designed in order to evaluate the flexural behavior of the wet joints in precast concrete slabs through four-point bending tests. This study investigates the effects of lap length, wet joint width, and water stop strips on the flexural behavior. The test results show that the ultimate bending capacity of the specimen with a lap length of 240 mm is 13.4% and 17.7% higher than that of the specimens with 160 mm and 80 mm. Water stop strips weaken the ductility of the specimen. The numerical model is established in ABAQUS finite element software and verified by the experimental results. Based on both test outcomes and finite element analysis, this study analyzes the deterioration effect of U-bars on the concrete within wet joints and proposes a calculation formula for flexural bending capacity that accounts for this deterioration. The proposed formula is shown to effectively predict the flexural capacity, since the theoretical predictions and the test results differ by less than 10%. Full article
(This article belongs to the Section Building Structures)
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Figure 1
<p>Contacted U-bars.</p>
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<p>Details of specimens (the unit of length is millimeters).</p>
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<p>Details of specimens (the unit of length is millimeters).</p>
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<p>The ratio λ (λ = overlap length/bar diameter).</p>
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<p>Details of joint layout (the unit of length is millimeters).</p>
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<p>Test setup (the unit of length is millimeters).</p>
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<p>Strain gauge arrangement.</p>
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<p>Load–deflection curve.</p>
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<p>Load–deflection curve.</p>
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<p>Crack patterns.</p>
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<p>Crack patterns.</p>
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<p>Crack and damage in L1 and L2.</p>
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<p>Crack in S2 (240 mm).</p>
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<p>Steel fracture (240 mm).</p>
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<p>Crack in specimen W.</p>
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<p>The steel strain in the U-bars inside the joint.</p>
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<p>The steel strain in the U-bars inside the joint.</p>
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<p>Finite element model.</p>
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<p>The concrete damage plastic model.</p>
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<p>Stress–strain laws.</p>
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<p>Deflection–load curves of finite element analysis compared to experiment.</p>
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<p>Deflection–load curves of finite element analysis compared to experiment.</p>
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<p>Crack pattern of finite element analysis.</p>
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<p>Comparison of strain between experiment and FEM.</p>
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<p>Parameterized analysis results.</p>
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<p>Failure model.</p>
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<p>Strut-and-tie model.</p>
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<p>Equivalent stress.</p>
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<p>Deterioration concrete model.</p>
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<p>Effective compressed height.</p>
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18 pages, 18531 KiB  
Article
Fatigue Life Analysis of Cyclone Separator Group Structure in a Reactor Device
by Yilian Shan, Jiye Sun, Xianglong Zhu, Yanhui Tian, Junyao Zhou, Yuzhe Ding, Benjie Ding, Jianke Du and Minghua Zhang
Materials 2025, 18(6), 1214; https://doi.org/10.3390/ma18061214 - 9 Mar 2025
Viewed by 344
Abstract
In the chlorination industry, the reactor is a crucial equipment in which the chlorination reaction takes place. However, when the reactor is subjected to complex conditions such as high temperatures (e.g., >200 °C) and high pressures (e.g., >10 MPa), its structural integrity is [...] Read more.
In the chlorination industry, the reactor is a crucial equipment in which the chlorination reaction takes place. However, when the reactor is subjected to complex conditions such as high temperatures (e.g., >200 °C) and high pressures (e.g., >10 MPa), its structural integrity is significantly compromised, leading to severe safety issues. In this study, the fatigue life of a reactor is analyzed, with particular focus on the fatigue behavior of the cyclone separator under varying working conditions, such as changes in the temperature, pressure, and chemical environment. Using finite element simulations under steady-state conditions and the S-N curve from fatigue testing, the fatigue life and potential weak points of the reactor under different amplitudes and vibration frequencies are analyzed and predicted. This analysis is conducted using a combined simulation approach with ABAQUS and Fe-Safe software, v 6.14. This work also considers the periodic vibrations at the base of the cyclone separator within the reactor. Fatigue simulations under different vibration conditions are performed to further assess the fatigue life of the reactor, providing a theoretical basis for the optimization of design and ensuring operational safety. In addition, the influence of welding zones on the fatigue life is discussed. The results indicate that the welding defects and stress concentration may cause the welded joint to become a critical weak point for fatigue failure. Therefore, the fatigue performance of the welding zone should be carefully considered during the design phase. Full article
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Figure 1

Figure 1
<p>Q345R steel specimen and welding specimen for fatigue test. (<b>a</b>) Schematic depicting the dimensions of the Q345R steel specimen. (<b>b</b>) Schematic depicting the dimensions of the welded Q345R steel specimen. (<b>c</b>) Q345R steel specimen. (<b>d</b>) Welded Q345R steel specimen.</p>
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<p>MTS 50 kN fatigue testing machine.</p>
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<p>S-N curve of Q345R steel specimen, welded specimen, and corrosion-exposed steel specimens.</p>
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<p>Structural diagram of cyclone separator.</p>
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<p>Schematic diagram of reactor structure.</p>
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<p>Boundary condition diagram.</p>
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<p>Reactor mesh diagram.</p>
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<p>Stress distribution of the main structures during steady-state operation of the reactor (unit: MPa).</p>
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<p>Displacement distribution of the structure during steady-state operation of the reactor (Unit: mm). (<b>a</b>) X-axis displacement distribution of the structure. (<b>b</b>) Y-axis displacement distribution of the structure. (<b>c</b>) Z-axis displacement distribution of the structure.</p>
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<p>Fatigue analysis process of reactor [<a href="#B27-materials-18-01214" class="html-bibr">27</a>].</p>
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<p>Vibration modes of the three frequencies (unit: mm). (<b>a</b>) Vibration mode of the reactor at a frequency of 1.2834 Hz. (<b>b</b>) Vibration mode of the reactor at a frequency of 2.4030 Hz. (<b>c</b>) Vibration mode of the reactor at a frequency of 2.8723 Hz.</p>
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<p>FOS distribution in the area above the cylinder in the reactor. (<b>a</b>) FOS distribution of the reactor (frequency: 1.2834 Hz; displacement: 10 mm along the X direction). (<b>b</b>) FOS distribution of the reactor (frequency: 2.4030 Hz; displacement: 10 mm along the X direction). (<b>c</b>) FOS distribution of the reactor (frequency: 2.8723 Hz; displacement: 10 mm along the X direction).</p>
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18 pages, 8223 KiB  
Article
Numerical Simulation Analysis of Lead Rubber Bearings (LRBs) Damage and Superstructure Response Under Near-Fault Earthquakes
by Yue Ren, Ruidong Wang, Wenfu He and Wenguang Liu
Buildings 2025, 15(5), 839; https://doi.org/10.3390/buildings15050839 - 6 Mar 2025
Viewed by 150
Abstract
Under the action of near fault earthquakes, the LRB bearings of long-period isolated buildings are prone to significant deformation and failure under compression shear conditions. Therefore, it is necessary to analyze the damage of LRB and its impact on the superstructure. Finite element [...] Read more.
Under the action of near fault earthquakes, the LRB bearings of long-period isolated buildings are prone to significant deformation and failure under compression shear conditions. Therefore, it is necessary to analyze the damage of LRB and its impact on the superstructure. Finite element analysis methodology was selected and Abaqus was used to simulate hysteresis curve of LRB and the separation between rubber layer and steel layer when horizontal deformation reaches 400%. A simplified four-stiffness isolation bearing model is proposed and applied to seismic isolation damage analysis on 8-story seismic structure under near-fault earthquakes. Damage on different positions and numbers of bearings are also compared. It concludes that under the compressive and shearing state, when the horizontal deformation of the isolator exceeds 300%, the stiffness enhancement section appears. Moreover, it is found that the damage of all LRBs show the most significant scale-up effect on acceleration and story drift. Full article
(This article belongs to the Section Building Structures)
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Figure 1
<p>Diagram of methodology.</p>
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<p>Finite element model of lead isolation bearing. (<b>a</b>) Assembly model; (<b>b</b>) Grid model.</p>
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<p>Stress–strain curves. (<b>a</b>) Rubber; (<b>b</b>) Lead; (<b>c</b>) Steel.</p>
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<p>Superstructure model.</p>
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<p>LRB400 arrangement plan.</p>
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<p>Isolated structure finite element model.</p>
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<p>Simulation loading curve.</p>
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<p>Comparison of hysteresis curve of LRB600: (<b>a</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 50%; (<b>b</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 100%; (<b>c</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 150%; (<b>d</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 200%; (<b>e</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 300%; (<b>f</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 400%.</p>
Full article ">Figure 8 Cont.
<p>Comparison of hysteresis curve of LRB600: (<b>a</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 50%; (<b>b</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 100%; (<b>c</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 150%; (<b>d</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 200%; (<b>e</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 300%; (<b>f</b>) Hysteresis curve and deformation of LRB600 under <span class="html-italic">γ</span> = 400%.</p>
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<p>Comparison of hysteresis curve of LRB600.</p>
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<p>Horizontal direction constitutive relation of LRB.</p>
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<p>Destruction analysis model and results: (<b>a</b>) LRB analysis model; (<b>b</b>) Side view of LRB destruction; (<b>c</b>) Top view of LRB destruction.</p>
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<p>Comparison of Abaqus/Standard and Abaqus/Explicit.</p>
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<p>Acceleration curve of the top layer of the superstructure. (<b>a</b>) Top-layer acceleration curve in working condition 1; (<b>b</b>) Top-layer acceleration curve in working condition 2; (<b>c</b>) Top-layer acceleration curve in working condition 3; (<b>d</b>) Top-layer acceleration curve in working condition 4; (<b>e</b>) Top-layer acceleration curve in working condition 5; (<b>f</b>) Top-layer acceleration curve in working condition 6.</p>
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<p>Peak acceleration of each floor.</p>
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<p>Story drift of each floor.</p>
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19 pages, 7569 KiB  
Article
Vibration Analysis of Shape Memory Alloy Enhanced Multi-Layered Composite Beams with Asymmetric Material Behavior
by Kosar Samadi-Aghdam, Pouya Fahimi, Hamid Shahsavari, Davood Rahmatabadi and Mostafa Baghani
Materials 2025, 18(5), 1181; https://doi.org/10.3390/ma18051181 - 6 Mar 2025
Viewed by 165
Abstract
This study develops a finite element solution to analyze the vibration response of multi-layer shape memory alloy (SMA) composite beams. Using Euler–Bernoulli beam motion equations with tension–compression asymmetry, based on Poorasadion’s model, the Newmark method and Newton–Raphson technique are employed. Validating the model [...] Read more.
This study develops a finite element solution to analyze the vibration response of multi-layer shape memory alloy (SMA) composite beams. Using Euler–Bernoulli beam motion equations with tension–compression asymmetry, based on Poorasadion’s model, the Newmark method and Newton–Raphson technique are employed. Validating the model against ABAQUS/Standard results for a homogeneous SMA beam shows good agreement. This research explores the dynamic characteristics of bi-layer and tri-layer SMA beams, presenting deflection–time, stress–strain, and velocity–deflection profiles. SMAs’ hysteresis property effectively reduces early-stage vibration amplitudes, and their energy-dissipating feature during phase transformations makes them promising for controlling dynamic performance in engineering applications. Full article
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Figure 1

Figure 1
<p>A typical beam element with forces and moments to derive motion equations.</p>
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<p>Solution algorithm for the proposed formulation.</p>
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<p>Geometry of the beam and the cross-section.</p>
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<p>History of the maximum deflection (<b>a</b>,<b>b</b>) and velocity (<b>c</b>,<b>d</b>) for the ASYM and SYM models and also for the proposed model and finite element simulations.</p>
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<p>Schematic of the tri-layer composite beam.</p>
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<p>Free vibration analysis of tri-layer SMA composite beam, (<b>a</b>) time history of the tri-layer beam tip deflections, (<b>b</b>) time history of the velocity of the free end of the beam, (<b>c</b>) strain–stress diagram of a point with 5 mm distance from the clamped end of the beam, (<b>d</b>) phase portrait of the free end of the beam, (<b>e</b>) deflection of the beam four individual times.</p>
Full article ">Figure 6 Cont.
<p>Free vibration analysis of tri-layer SMA composite beam, (<b>a</b>) time history of the tri-layer beam tip deflections, (<b>b</b>) time history of the velocity of the free end of the beam, (<b>c</b>) strain–stress diagram of a point with 5 mm distance from the clamped end of the beam, (<b>d</b>) phase portrait of the free end of the beam, (<b>e</b>) deflection of the beam four individual times.</p>
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<p>Contour plot of strain for ASPM and SSPM models.</p>
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<p>Size parameter effect on time history of the tri-layer beam tip deflections for size parameter <math display="inline"><semantics> <mrow> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mi>h</mi> <mi>L</mi> </mfrac> </mstyle> <mo>=</mo> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mn>1</mn> <mn>8</mn> </mfrac> </mstyle> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mi>h</mi> <mi>L</mi> </mfrac> </mstyle> <mo>=</mo> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mn>1</mn> <mrow> <mn>10</mn> </mrow> </mfrac> </mstyle> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mi>h</mi> <mi>L</mi> </mfrac> </mstyle> <mo>=</mo> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mn>1</mn> <mrow> <mn>12</mn> </mrow> </mfrac> </mstyle> </mrow> </semantics></math>.</p>
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<p>Schematic of the bi-layer SMA beam.</p>
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<p>Free vibration analysis of bi-layer SMA composite beam, (<b>a</b>) time history of the bi-layer beam tip deflections, (<b>b</b>) time history of the velocity of the free end of the beam, (<b>c</b>) strain–stress diagram of a point with 5 mm distance from the clamped end of the beam, (<b>d</b>) phase portrait of the free end of the beam, (<b>e</b>) deflection of the beam four individual times.</p>
Full article ">Figure 10 Cont.
<p>Free vibration analysis of bi-layer SMA composite beam, (<b>a</b>) time history of the bi-layer beam tip deflections, (<b>b</b>) time history of the velocity of the free end of the beam, (<b>c</b>) strain–stress diagram of a point with 5 mm distance from the clamped end of the beam, (<b>d</b>) phase portrait of the free end of the beam, (<b>e</b>) deflection of the beam four individual times.</p>
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<p>Contour plots of the strain for ASPM and SSPM models.</p>
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<p>Time history of the bi-layer beam tip deflections for different amplitude of impulse loading.</p>
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21 pages, 11242 KiB  
Article
Dynamic Response Analysis of Large-Diameter Monopile Foundation Under Ice Load
by Shuxing Liu, Shengyi Cong, Xianzhang Ling and Liang Tang
Sustainability 2025, 17(5), 2300; https://doi.org/10.3390/su17052300 - 6 Mar 2025
Viewed by 169
Abstract
This study investigates the dynamic response of large-diameter monopile foundations subjected to ice loads, emphasizing sustainable design in cold-region offshore wind energy development. Through a combined ice–structure–soil model test and subsequent development of a three-dimensional ice–OWT–soil system model using Abaqus software 2022, this [...] Read more.
This study investigates the dynamic response of large-diameter monopile foundations subjected to ice loads, emphasizing sustainable design in cold-region offshore wind energy development. Through a combined ice–structure–soil model test and subsequent development of a three-dimensional ice–OWT–soil system model using Abaqus software 2022, this research addresses the sustainability of infrastructure exposed to harsh environmental conditions. The dynamic ice loads are simulated using the coupled CEM–FEM approach, while the Mohr–Coulomb model calculates soil–structure interactions. The calibration and verification processes include comparisons of simulated ice forces, ice-crushing processes, and pile deflections with experimental results. This study comprehensively assesses the effects of ice velocity and thickness on ice actions, as well as the monopile’s top displacement, shear force, and bending moment. The findings indicate that ice thickness significantly influences the dynamic response more than ice velocity, guiding the design toward more sustainable and resilient offshore wind infrastructures. Additionally, a semi-empirical calculation method incorporating the aspect ratio effect is proposed, enhancing the predictive accuracy and sustainability of large-diameter monopile foundations, as validated against field monitoring data from the Norströmsgrund lighthouse. Compared to traditional ice pressure calculation methods, the proposed approach focuses on the influence of the aspect ratio of large-diameter monopile foundations, enabling a more realistic and objective assessment of ice load calculations for OWTs in cold regions. The results demonstrate the efficacy of the proposed approach and offer a new perspective for the design of OWT structures under ice loads. Full article
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<p>Constitutive curve of ice model: (<b>a</b>) bulk elements; (<b>b</b>) cohesive elements.</p>
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<p>Numerical model sketch: (<b>a</b>) schematic diagram of cohesive element model; (<b>b</b>) coupled CEM–FEM model of ice.</p>
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<p>Numerical model of ice–OWT–soil system: (<b>a</b>) ice–OWT–soil interaction coupling model; (<b>b</b>) ice–OWT interaction model.</p>
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<p>Ice–structure–soil model test: (<b>a</b>) ice-pushing system; (<b>b</b>) DUT-1 model ice.</p>
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<p>(<b>a</b>–<b>d</b>) Detailed simulation of ice–pile interaction.</p>
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<p>Comparisons of time histories of dynamic ice force between numerical result and experiment result.</p>
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<p>Soil–structure interaction model: (<b>a</b>) finite element model; (<b>b</b>) mesh configuration (after Zou et al. [<a href="#B20-sustainability-17-02300" class="html-bibr">20</a>]).</p>
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<p>(<b>a</b>) Mises stress of soils; (<b>b</b>) pile displacement under various loads [<a href="#B20-sustainability-17-02300" class="html-bibr">20</a>,<a href="#B40-sustainability-17-02300" class="html-bibr">40</a>].</p>
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<p>Ice force histories from the simulations with different mesh sizes.</p>
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<p>The mean, std., and maximum of ice forces with different mesh sizes.</p>
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<p>Time histories and frequency spectra of ice force for different ice velocities: (<b>a</b>) time series of ice force; (<b>b</b>) frequency spectrum of ice force.</p>
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<p>Time histories and frequency spectra of monopile top displacement for different ice velocities: (<b>a</b>) time series of monopile top displacement; (<b>b</b>) frequency spectrum of monopile top displacement.</p>
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<p>Time history and statistics results of the shear force and bending moment for different ice velocities: (<b>a</b>) time series of shear force; (<b>b</b>) statistics results of the shear force; (<b>c</b>) time series of bending moment; (<b>d</b>) statistics results of the bending moment.</p>
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<p>Time histories and frequency spectra of ice force for different ice thickness: (<b>a</b>) time series of ice force; (<b>b</b>) frequency spectrum of ice force.</p>
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<p>Time histories and frequency spectra of monopile top displacement for different ice thicknesses: (<b>a</b>) time series of monopile top displacement; (<b>b</b>) frequency spectrum of monopile top displacement.</p>
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<p>Time history and statistics results of the shear force and bending moment for different ice thickness: (<b>a</b>) time series of shear force; (<b>b</b>) statistics results of the shear force; (<b>c</b>) time series of bending moment; (<b>d</b>) statistics results of the bending moment.</p>
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<p>Comparison of extreme ice forces between the numerical results and the calculated values according to standards.</p>
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<p>Trend of <span class="html-italic">p</span><sub>G</sub> under different aspect ratios (D/h).</p>
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<p>Comparison of calculated global ice pressure with field measurements.</p>
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28 pages, 9825 KiB  
Article
Study on the Application and Deformation Characteristics of Construction Waste Recycled Materials in Highway Subgrade Engineering
by Yuan Mei, Hongping Lu, Xueyan Wang, Bingyu Zhou, Ziyang Liu and Lu Wang
Buildings 2025, 15(5), 835; https://doi.org/10.3390/buildings15050835 - 6 Mar 2025
Viewed by 112
Abstract
It is difficult to meet environmental requirements via the coarse treatment methods of landfilling and open-air storage of construction waste. At the same time, the consumption of building materials in highway engineering is enormous. Using construction waste as a filling material for proposed [...] Read more.
It is difficult to meet environmental requirements via the coarse treatment methods of landfilling and open-air storage of construction waste. At the same time, the consumption of building materials in highway engineering is enormous. Using construction waste as a filling material for proposed roads has become a research hotspot in recent years. This paper starts with basic performance tests of recycled construction waste materials, and then moves on to laboratory experiments conducted to obtain the road performance of the recycled materials, the testing of key indicators of post-construction filling quality of the roadbed, and analyses of the deformation pattern of roadbed filled with construction waste. Additionally, the ABAQUS finite element software was used to establish a numerical model for roadbed deformation and analyze the roadbed deformation under different compaction levels and vehicle load conditions. The experimental results show that the recycled material has a moisture content of 8.5%, water absorption of 11.73%, and an apparent density of 2.61 g/cm3, while the liquid limit of fine aggregates is 20% and the plasticity index is 5.4. Although the physical properties are slightly inferior to natural aggregates, its bearing ratio (25–55%) and low expansion characteristics meet the requirements for high-grade highway roadbed filling materials. The roadbed layer with a loose compaction of 250 mm, after eight passes of rolling, showed a settlement difference of less than 5 mm, with the loose compaction coefficient stabilizing between 1.15 and 1.20. Finite element simulations indicated that the total settlement of the roadbed stabilizes at 20–30 mm, and increasing the compaction level to 96% can reduce the settlement by 2–4%. Vehicle overload causes a positive correlation between the vertical displacement and shear stress in the base layer, suggesting the need to strengthen vehicle load control. The findings provide theoretical and technical support for the large-scale application of recycled construction waste materials in roadbed engineering. Full article
(This article belongs to the Topic Sustainable Building Materials)
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<p>Technical route diagram.</p>
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<p>Boundary moisture content test.</p>
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<p>Particle gradation curve.</p>
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<p>Standardized compaction test procedure.</p>
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<p>Effect of moisture content change on compacted specimens. (<b>a</b>) Water content 10%. (<b>b</b>) Water content 12%. (<b>c</b>) Water content 14%. (<b>d</b>) Water content 16%. (<b>e</b>) Water content 18%.</p>
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<p>Relationship between dry density and moisture content of coarse and fine aggregates in different proportions.</p>
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<p>Relationship between mixture content and compaction test results.</p>
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<p>California Bearing Ratio test procedure. (<b>a</b>) Specimen preparation. (<b>b</b>) Immersion of the specimen in water. (<b>c</b>) Specimen under pressure. (<b>d</b>) Specimen destruction.</p>
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<p>Test diagram of construction waste recycled materials for subgrade fill. (<b>a</b>) Test section. (<b>b</b>) Design of highway subgrade sections.</p>
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<p>Construction process of construction waste subgrade.</p>
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<p>Layout of compaction test points. (<b>a</b>) Compaction test cross-section. (<b>b</b>) Compaction test plan. (<b>c</b>) Compaction test site layout.</p>
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<p>EVD values corresponding to different compaction levels.</p>
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<p>Beckman beam measurement point layout and detection. (<b>a</b>) Elevation view of the detection point. (<b>b</b>) Plan view of detection points.</p>
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<p>Observation point layout.</p>
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<p>Settlement variation curve of the subgrade during the construction period due to construction waste. (<b>a</b>) Settlement variation in the left side of the subgrade. (<b>b</b>) Settlement variation in the right side of the subgrade. (<b>c</b>) Settlement of the subgrade cross-section.</p>
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<p>Numerical model of the subgrade.</p>
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<p>Boundary conditions.</p>
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<p>Displacement cloud map of roadbed. (<b>a</b>) Horizontal displacement of roadbed (X direction). (<b>b</b>) Vertical displacement of roadbed (Y direction).</p>
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<p>Roadbed deformation cloud map corresponding to different compaction degrees. (<b>a</b>) Cloud map of roadbed settlement when compaction degree is 90%. (<b>b</b>) Cloud map of roadbed settlement when compaction degree is 93%. (<b>c</b>) Cloud map of roadbed settlement when compaction degree is 96%.</p>
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<p>Loading area.</p>
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<p>Grid division.</p>
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<p>Vertical displacement corresponding to different loads. (<b>a</b>) Vertical displacement corresponding to a load of 100 kN. (<b>b</b>) Vertical displacement corresponding to a load of 120 kN. (<b>c</b>) Vertical displacement corresponding to a load of 160 kN. (<b>d</b>) Vertical displacement corresponding to a load of 200 kN.</p>
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<p>Load and vertical displacement of roadbed. (<b>a</b>) Vertical displacement curve corresponding to different loads on the top surface of the base. (<b>b</b>) Vertical displacement curve corresponding to different loads at the top surface of the base layer (0.38 m). (<b>c</b>) Vertical displacement curve corresponding to different loads at the top of the roadbed (0.58 m).</p>
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<p>Effect of load on shear stress.</p>
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18 pages, 11112 KiB  
Article
Dynamic Compressive Behavior, Constitutive Modeling, and Complete Failure Criterion of 30 Vol.% B4C/2024Al Composite
by Qiang Yan, Zhihong Zhao, Tian Luo, Feng Li, Jianjun Zhao, Zhenlong Chao, Sanfeng Liu, Yong Mei and Fengjun Zhou
Materials 2025, 18(5), 1170; https://doi.org/10.3390/ma18051170 - 6 Mar 2025
Viewed by 180
Abstract
This study investigated the compressive behavior of 30 vol.% boron carbide (B4C)/2024 aluminum (Al) composites under quasi-static and dynamic loading at different temperatures. Building on the experimental findings, the Johnson–Cook (JC) model was modified, and a complete failure criterion was proposed. [...] Read more.
This study investigated the compressive behavior of 30 vol.% boron carbide (B4C)/2024 aluminum (Al) composites under quasi-static and dynamic loading at different temperatures. Building on the experimental findings, the Johnson–Cook (JC) model was modified, and a complete failure criterion was proposed. These were validated in Abaqus employing the user subroutine for hardening (VUHARD), which incorporated both the modified JC (MJC) model and the complete failure criterion. Experimental results revealed that strain softening was an important feature of the stress–strain curve. The analysis of mechanisms contributing to yield strength revealed that Taylor and load transfer mechanisms dominated, accounting for 89.6% of the total enhancement. Microstructural analysis identified particle fracture and matrix damage were the primary mechanisms driving material failure. Microcracks mainly propagated through the matrix and interface or directly through the ceramic particles and the matrix. The MJC model demonstrated high accuracy in describing the plastic deformation behavior of the composite, with a mean absolute error (MAE) below 15% under dynamic loading. Further simulation confirmed that finite element analyses using the VUHARD subroutine accurately captured the plastic deformation and crack propagation behaviors of the composite under dynamic loading. This study offers a novel approach to describe the plastic deformation and failure behaviors of ceramic-reinforced aluminum matrix composites under dynamic loading conditions. Full article
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<p>Fabrication, Processing, and Compression Testing of 30 vol.% B<sub>4</sub>C/2024Al Composite. (<b>a</b>) Fabrication through the pressure infiltration process. (<b>b</b>) Schematic of the quasi-static compression test configuration. (<b>c</b>) Schematic of the SHPB test configuration.</p>
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<p>Flowchart of VUHARD subroutine development.</p>
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<p>Processed samples and Compression test results. (<b>a</b>) Low- and high-resolution SEM images of the processed samples. (<b>b</b>) Strain rate versus time curves in SHPB testing at 298.15 K. (<b>c</b>–<b>f</b>) True stress–strain curves at strain rates of 0.01/s, 2000/s, 4000/s, and 6000/s.</p>
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<p>Strengthening mechanisms of the 30 vol.% B<sub>4</sub>C/2024Al composite. (<b>a</b>) Calculated contributions of different strengthening mechanisms to the yield strength enhancement. (<b>b</b>) Comparison of the linear superposition and the sum of squares method for predicting yield strength.</p>
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<p>Damage progression and macro-morphology of the 30 vol.% B<sub>4</sub>C/2024Al composite. (<b>a</b>–<b>c</b>) High-speed images of dynamic compression at 298.15 K and strain rates of 2000/s, 4000/s, and 6000/s. (<b>d</b>) Macro-damage morphology of recovered specimens after compression.</p>
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<p>Damage modes of recovered specimens. (<b>a</b>) 0.01/s, 298.15 K. (<b>b</b>) 6000/s, 298.15 K. (<b>c</b>) 0.01/s, 723.15 K. (<b>d</b>) Two microcrack development modes.</p>
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<p>Construction and parameter calibration of the MJC constitutive equation. (<b>a</b>,<b>b</b>) Evaluation of the coupled effects of temperature and strain rate on flow stress, and determination of the temperature sensitivity coefficient <b><span class="html-italic">s</span></b><span class="html-italic">,</span> and the strain rate sensitivity coefficient <span class="html-italic">m</span>. (<b>c</b>) Calibration of the yield strength parameter <span class="html-italic">A</span> under 0.01/s and 298.15 K. (<b>d</b>) Calibration of parameters <span class="html-italic">B</span>, <span class="html-italic">C</span>, <span class="html-italic">p</span>, and <span class="html-italic">q</span>. (<b>e</b>) Calibration of parameter <span class="html-italic">n</span>. (<b>f</b>) Calibration of parameters <span class="html-italic">C</span><sub>1</sub>, <span class="html-italic">C</span><sub>2</sub>, and <span class="html-italic">C</span><sub>3</sub>.</p>
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<p>Calibration of parameters for the complete failure equation. (<b>a</b>) Strain energy density under experimental conditions. (<b>b</b>) Calibration of parameters <span class="html-italic">D</span><sub>5</sub> and <span class="html-italic">D</span><sub>6</sub>. (<b>c</b>) Calibration of parameters <span class="html-italic">D</span><sub>1</sub>, <span class="html-italic">D</span><sub>2</sub>, <span class="html-italic">D</span><sub>3</sub>, and <span class="html-italic">D</span><sub>4</sub>.</p>
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<p>Fitting results of the MJC constitutive equation. (<b>a</b>–<b>d</b>) Comparison of the stress–strain relationships predicted by the MJC with experimental data at strain rates of 0.01/s, 2000/s, 4000/s, and 6000/s. (<b>e</b>) Mean absolute error of the MJC predictions under dynamic loading conditions.</p>
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<p>Stress–time loading curves at different strain rates.</p>
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<p>Validation of VUHARD subroutine in SHTB finite element analysis. (<b>a</b>–<b>c</b>) Damage morphologies from finite element analysis and experiments at strain rates of 2000/s, 4000/s, and 6000/s. (<b>d</b>–<b>f</b>) Comparison of the stress–strain curves from finite element analysis and experiments at strain rates of 2000/s, 4000/s, and 6000/s.</p>
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14 pages, 4444 KiB  
Article
A Theoretical and Numerical Approach to Ensure Ductile Failure in Strengthened Reinforced Concrete Slabs with Fiber-Reinforced Polymer Sheets
by Huy Q. Nguyen and Jung J. Kim
Buildings 2025, 15(5), 831; https://doi.org/10.3390/buildings15050831 - 5 Mar 2025
Viewed by 349
Abstract
While fiber-reinforced polymer (FRP) sheets effectively enhance the flexural strength of reinforced concrete (RC) slabs, excessive flexural strengthening can reduce ductility and lead to brittle failure. This study provides an overview of the failure limits for the end spans of continuous RC slabs, [...] Read more.
While fiber-reinforced polymer (FRP) sheets effectively enhance the flexural strength of reinforced concrete (RC) slabs, excessive flexural strengthening can reduce ductility and lead to brittle failure. This study provides an overview of the failure limits for the end spans of continuous RC slabs, considering the relationship between moment and shear capacities. A design approach for maximizing the strength contribution and amount of carbon FRP (CFRP) while ensuring ductile failure in strengthened slabs was developed and refined based on ACI standard recommendations. The failure mode of the strengthened slab was validated through numerical analysis using Abaqus software by further investigating the stress distribution of flexural members. Analytical results indicated that a 0.15 mm thick CFRP layer could enhance the nominal failure load by 148% while preserving desirable ductile failure behavior, demonstrating the effectiveness and feasibility of the proposed approach. Full article
(This article belongs to the Section Building Materials, and Repair & Renovation)
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<p>Coefficients for estimating moments and shears in continuous slabs supported by column based on ACI 318M [<a href="#B44-buildings-15-00831" class="html-bibr">44</a>].</p>
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<p>Failure regions for the end span in continuous slab based on the moment and shear capacities.</p>
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<p>Reinforcement details of the strengthened slab (unit: mm).</p>
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<p>Strain and stress distribution in slab sections at the limit state.</p>
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<p>Predict the end span failure mode based on moment resistances.</p>
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<p>CFRP-strengthened RC slab model.</p>
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<p>Evaluation of mesh density convergence.</p>
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<p>Stress–strain behavior of concrete.</p>
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<p>Predicting failure modes for the strengthened RC slab: (<b>a</b>) brittle failure; (<b>b</b>) ductile failure.</p>
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<p>Comparison of numerical and theoretical predictions for strengthened and unstrengthened slab behavior.</p>
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<p>CFRP strain at failure in the strengthened slab (<b>a</b>) 1 mm thick CFRP; (<b>b</b>) 0.15 mm thick CFRP.</p>
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<p>Stress distribution at ultimate failure for the strengthened slab with 1 mm thick CFRP: (<b>a</b>) steel bar and (<b>b</b>) CFRP sheet.</p>
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<p>Stress distribution at yielding for the strengthened slab with 0.15 mm thick CFRP: (<b>a</b>) steel bar and (<b>b</b>) CFRP sheet.</p>
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<p>CFRP stress distribution at ultimate failure for the strengthened slab with 0.15 mm thick CFRP.</p>
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24 pages, 7243 KiB  
Article
Optimization Design of Flexible Net Capture System for Low, Slow, and Small Unmanned Aerial Vehicles Based on Improved Multi-Objective Wolf Pack Algorithm
by Ran Xu, Qiang Peng and Husheng Wu
Drones 2025, 9(3), 190; https://doi.org/10.3390/drones9030190 - 4 Mar 2025
Viewed by 254
Abstract
In response to the increasing safety concerns posed by low, slow, and small unmanned aerial vehicles (UAVs), the use of flexible nets for interception emerges as a promising solution due to its high tolerance, minimal requirements, and cost-effectiveness. To enhance the effectiveness of [...] Read more.
In response to the increasing safety concerns posed by low, slow, and small unmanned aerial vehicles (UAVs), the use of flexible nets for interception emerges as a promising solution due to its high tolerance, minimal requirements, and cost-effectiveness. To enhance the effectiveness of the flexible net capture system for these types of UAVs, an optimization of the system’s parameters is conducted. A dynamic model of the flexible net capture system is developed, and its deployment process is simulated and analyzed through a combination of ABAQUS 2022/Explicit and MATLAB R2020b software. The coverage rate and hang time are proposed as the key performance indicators for quantitatively assessing the interception capabilities of the rope net. A mathematical model is formulated to optimize the capture system parameters, considering both spatial and temporal tolerances. The Multi-objective Wolf Pack Algorithm, which incorporates an Elite Leadership Strategy and a crowding distance-based population update mechanism, is utilized to optimize the design variables. This approach leads to the derivation of the optimized design parameters for the flexible net. Ultimately, the optimal parameter configuration for the flexible net capture system is achieved through the application of the Multi-objective Wolf Pack Algorithm to the design variables. This optimization ensures the system’s peak performance in intercepting low, slow, and small UAVs. Full article
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<p>Work illustration of the flexible net capture system for low, slow and small UAVs.</p>
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<p>Simplified mechanical model of the flexible net. (<b>a</b>) Rope net configuration; (<b>b</b>) Half-spring-damping model.</p>
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<p>Diagram of the forces acting on the flexible rope net. (<b>a</b>) Internal forces acting on the rope segments; (<b>b</b>) external forces acting on the rope segments.</p>
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<p>Modeling simulation process.</p>
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<p>Finite element model of flexible rope net.</p>
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<p>Simulation diagram of the deployment process of the flexible net. (<b>a</b>) 0.05 s; (<b>b</b>) 0.1 s; (<b>c</b>) 0.13 s; (<b>d</b>) 0.17 s; (<b>e</b>) 0.24 s.</p>
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<p>The curve of the deployment area of the flexible net changing with time.</p>
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<p>Net spread area of flexible net.</p>
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<p>Effective interception area of flexible net.</p>
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<p>Schematic diagram of the successful interception of the UAV by the flexible net.</p>
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<p>Population non-dominated rank.</p>
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<p>Population Position after Elite Leadership.</p>
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<p>Flow chart of optimization design.</p>
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<p>Initial population distribution in optimization design space.</p>
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<p>Initial solution set.</p>
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<p>Final population distribution in optimization design space.</p>
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<p>Optimal Pareto solution set.</p>
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<p>Schematic diagram of the flexible net capture envelope surface.</p>
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<p>Comparison of the flexible net capture envelope surface among frontier solutions C, E and the test value.</p>
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22 pages, 15374 KiB  
Article
Case Study on Response Characteristic of Surroundings Induced by a Covered Semi-Top-Down Excavation with Synchronous Construction of the Superstructure and Substructure
by Liyun Li, Zixuan Li, Ling Lei, Zhuyan Li, Haonan Jiang and Yunhao Gao
Appl. Sci. 2025, 15(5), 2739; https://doi.org/10.3390/app15052739 - 4 Mar 2025
Viewed by 150
Abstract
Relying on a foundation pit project leveraging the covered semi-top-down method with synchronous construction of the superstructure and substructure in Beijing, the whole process of construction was simulated by using ABAQUS finite-element software. The impact of the whole construction on the surrounding ground, [...] Read more.
Relying on a foundation pit project leveraging the covered semi-top-down method with synchronous construction of the superstructure and substructure in Beijing, the whole process of construction was simulated by using ABAQUS finite-element software. The impact of the whole construction on the surrounding ground, the adjacent building, and the retaining structure were studied, and the influence of the existing building, the strength of diaphragm wall, and the construction process were carried out. As shown from the results, the foundation pit and the existing building are in a safe state during the whole construction process. The ground settlement shows an obvious groove shape. The deformation of the diaphragm wall has obvious spatial effects, which changes from “single peak” to “double peaks”. The maximum horizontal displacement of strata behind the diaphragm wall occurs at a depth of 22.5 m, which is 1.4–2.0 times the top horizontal displacement. The presence of existing buildings reduced the ground settlement between the buildings and the excavation surface. The construction process has little impact on the settlement of adjacent existing buildings, which can be adjusted appropriately. Full article
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<p>Excavation site and the monitoring points. In which, the excavation sequence for each depth of foundation pit is to excavate Sec1 first, then Sec2, and finally Sec3. The core tube is a part of the newly constructed structure.</p>
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<p>The construction processes of synchronous construction of the superstructure and substructure.</p>
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<p>The FEM model. (<b>a</b>) Excavation and surrounding site; (<b>b</b>) structure in the excavation area.</p>
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<p>Results of monitoring data and numerical simulation of ground settlement. (<b>a</b>) DB-1; (<b>b</b>) DB-2.</p>
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<p>History curves of the settlement of surrounding buildings. (<b>a</b>) JC-1; (<b>b</b>) JC-2.</p>
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<p>Displacement contour maps of diaphragm wall. (<b>a</b>) The X-direction; (<b>b</b>) the Y-direction.</p>
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<p>Horizontal displacement of diaphragm wall at section III–III.</p>
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<p>Horizontal displacement of the diaphragm wall at different monitoring sections.</p>
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<p>Bending moment of diaphragm wall at section III–III.</p>
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<p>Horizontal displacement contour maps of the core tubes. (<b>a</b>) The X-direction; (<b>b</b>) the Y-direction.</p>
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<p>Displacement contour map of the integrated piles and columns.</p>
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<p>Stress contour maps of the roof of the first underground floor. (<b>a</b>) Process 4; (<b>b</b>) process 5; (<b>c</b>) process 6; (<b>d</b>) process 7; (<b>e</b>) process 8; (<b>f</b>) process 9; (<b>g</b>) process 10.</p>
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<p>Stress contour maps of the roof of the first underground floor. (<b>a</b>) Process 4; (<b>b</b>) process 5; (<b>c</b>) process 6; (<b>d</b>) process 7; (<b>e</b>) process 8; (<b>f</b>) process 9; (<b>g</b>) process 10.</p>
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<p>Bending moment contour maps of the roof of the first underground floor. (<b>a</b>) The X-direction; (<b>b</b>) the Y-direction.</p>
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<p>Cloud map of surrounding ground settlement when the excavated depth is 6.7 m.</p>
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<p>Ground settlement trough curves. (<b>a</b>) Section I–I; (<b>b</b>) section II–II; (<b>c</b>) section III–III; (<b>d</b>) section IV–IV; (<b>e</b>) section V–V; (<b>f</b>) section VI–VI; (<b>g</b>) section VII–VII; and (<b>h</b>) monitoring sections.</p>
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<p>The horizontal displacement of strata behind the wall.</p>
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<p>History curves of the settlement of existing buildings.</p>
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<p>Horizontal displacement of diaphragm wall. (<b>a</b>) Section III–III; (<b>b</b>) section VII–VII.</p>
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<p>Ground settlement under different building loads. (<b>a</b>) Section III–III; (<b>b</b>) section VII–VII.</p>
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<p>Horizontal displacement of the diaphragm wall for different conditions. (<b>a</b>) Section V–V; (<b>b</b>) section VII–VII.</p>
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<p>Settlement of existing buildings for different conditions. (<b>a</b>) JC-1; (<b>b</b>) JC-2.</p>
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15 pages, 5156 KiB  
Article
Finite Element Analysis of Stress Distribution in Monolithic High-Translucency Zirconia Dental Prostheses
by Fernando Araújo da Costa Ward, Luciano Pessanha Moreira, Pedro Araújo da Costa Ward, Paula Cipriano da Silva, Manuel Fellipe Rodrigues Pais Alves and Claudinei Santos
Oral 2025, 5(1), 15; https://doi.org/10.3390/oral5010015 - 3 Mar 2025
Viewed by 265
Abstract
Background/Objectives: High-translucency zirconia is a dental ceramic offering excellent aesthetic results but with mechanical limitations restricting its applications. This study aimed to simulate the mechanical behavior of anatomical dental prostheses made from high-translucency zirconia using the finite element method (FEM) to assess [...] Read more.
Background/Objectives: High-translucency zirconia is a dental ceramic offering excellent aesthetic results but with mechanical limitations restricting its applications. This study aimed to simulate the mechanical behavior of anatomical dental prostheses made from high-translucency zirconia using the finite element method (FEM) to assess the material’s reliability. Methods: Samples of high-translucency zirconia were compacted, sintered, and characterized for relative density. Structural and microstructural analyses were performed using X-ray diffraction (XRD) and scanning electron microscopy (SEM). Its mechanical properties, including hardness, fracture toughness, and flexural strength, were measured. Additionally, elastic parameters such as Young’s modulus and Poisson’s ratio were determined using the impulse excitation technique and subsequently employed in numerical simulations under various masticatory loads (50 to 500 N). These simulations modeled an anatomical molar (tooth 26) using the HyperMesh and ABAQUS codes, applying loads from three directions: vertical, angular (45°), and horizontal, at different points on the prosthesis. Results: The sintered zirconia ceramics exhibited excellent densification and a microstructure composed of cubic and tetragonal grains (c-ZrO2 and t-ZrO2). The measured properties included a hardness of 1315 ± 48 HV, fracture toughness of 3.7 ± 0.2 MPam1/2, and flexural strength of 434 ± 67 MPa. Elastic parameters were determined as a Young’s modulus of 192.2 ± 4.8 GPa and a Poisson’s ratio of 0.31. Numerical simulations demonstrated that vertically applied loads of 500 N resulted in a maximum stress of approximately 299.2 MPa, horizontal stress reached 320.8 MPa at a 200 N load, and angular stress peaked at 447.3 MPa under a 350 N load. These findings indicate that the material can safely withstand these conditions without failure. Conclusions: Within the limits of this investigation, the methodology proved to be an effective tool for predicting the mechanical behavior of new dental ceramics. For high-translucency zirconia, the material demonstrated high reliability under masticatory vertical loads up to 500 N, angular loads up to 350 N, and horizontal loads up to 200 N. Full article
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Figure 1
<p>Geometry of the first molar (tooth 26) obtained through 3D digital scanning: (<b>a</b>) occlusal view, (<b>b</b>) bottom view, (<b>c</b>) finite element mesh, and (<b>d</b>) labeled occlusal view.</p>
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<p>Optimized finite element mesh of the first molar (tooth 26): (<b>a</b>) loading application regions and (<b>b</b>) interior layered mesh refinement.</p>
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<p>Model assembly: upper left first molar (tooth 26) with a fixed base.</p>
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<p>(<b>a</b>) XRD pattern and (<b>b</b>) SEM micrograph of 5Y-PSZ sintered samples.</p>
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<p>Absolute maximum principal stress distributions (MPa) under 500 N loading conditions: (<b>a</b>) vertical, (<b>b</b>) horizontal, and (<b>c</b>) angular.</p>
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<p>Maximum principal stress distributions (MPa) obtained from the isolated (<b>left</b>) and assembled (<b>right</b>) molar FEMs under 500 N loading conditions: (<b>a</b>) vertical, (<b>b</b>) horizontal, and (<b>c</b>) angular.</p>
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<p>Tensile and compressive stress regions determined for horizontal loading of 500 N.</p>
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<p>Maximum (<b>a</b>) and minimum (<b>b</b>) principal stress (MPa) obtained from the isolated molar model under 500 N loading conditions: (<b>1</b>) vertical, (<b>2</b>) horizontal, and (<b>3</b>) diagonal.</p>
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<p>Risk-of-failure predictions based on the Mohr–Coulomb criterion for the third molar (tooth 26) prosthesis FEM using 5Y-PSZ dental ceramics under different loading conditions.</p>
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<p>Risk of failure based on the Mohr–Coulomb yield criterion: (<b>a</b>) vertical load (500 N), (<b>b</b>) horizontal load (200 N), and (<b>c</b>) angular load (350 N).</p>
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27 pages, 8299 KiB  
Article
Monte Carlo Micro-Stress Field Simulations in Flax/E-Glass Composite Laminae with Non-Circular Flax Fibres
by Nenglong Yang, Zhenmin Zou, Constantinos Soutis, Prasad Potluri and Kali Babu Katnam
Polymers 2025, 17(5), 674; https://doi.org/10.3390/polym17050674 - 2 Mar 2025
Viewed by 242
Abstract
This study explores the mechanical behaviour of intra-laminar hybrid flax/E-glass composites, focusing on the role of micro-scale irregularities in flax fibres. By employing computational micromechanics and Monte Carlo simulations, it analyses the influence of flax fibre geometry and elastic properties on the performance [...] Read more.
This study explores the mechanical behaviour of intra-laminar hybrid flax/E-glass composites, focusing on the role of micro-scale irregularities in flax fibres. By employing computational micromechanics and Monte Carlo simulations, it analyses the influence of flax fibre geometry and elastic properties on the performance of hybrid and non-hybrid composites. A Non-Circular Fibre Distribution (NCFD) algorithm is introduced to generate microstructures with randomly distributed non-circular flax and circular E-glass fibres, which are then modelled using a 3D representative volume element (RVE) model developed in Python 2.7 and implemented with Abaqus/Standard. The RVE dimensions were specified as ten times the mean characteristic length of flax fibres (580 μm) for the width and length, while the thickness was defined as one-tenth the radius of the E-glass fibre. Results show that Monte Carlo simulations accurately estimate the effect of fibre variabilities on homogenised elastic constants when compared to measured values and Halpin-Tsai predictions, and they effectively evaluate the fibre/matrix interfacial stresses and von Mises matrix stresses. While these variabilities minimally affect the homogenised properties, they increase the presence of highly stressed regions, especially at the interface and matrix of flax/epoxy composites. Additionally, intra-laminar hybridisation further increases local stress in these critical areas. These findings improve our understanding of the relationship between the natural fibre shape and mechanical performance in flax/E-glass composites, providing valuable insights for designing and optimising advanced composite materials to avoid or delay damage, such as matrix cracking and splitting, under higher applied loads. Full article
(This article belongs to the Special Issue Structure, Characterization and Application of Bio-Based Polymers)
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Figure 1
<p>Representative microstructures of hybrid and non-hybrid composites created using the NCFD algorithm, showing the effects of varying flax fibre shapes and the specified fibre volume fractions for flax, E-glass, and matrix (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>f</mi> <mi>F</mi> </mrow> </msub> <mo>,</mo> <msub> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>f</mi> <mi>E</mi> </mrow> </msub> <mo>,</mo> <mi>V</mi> </mrow> <mrow> <mi>m</mi> </mrow> </msub> </mrow> </semantics></math>) as follows: (<b>a</b>) (0.48, 0.12, 0.40), (<b>b</b>) (0.48, 0.12, 0.40), (<b>c</b>) (0.60, 0, 0.40), (<b>d</b>) (0.60, 0, 0.40).</p>
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<p>The mean homogenised elastic constants computed from eight Monte Carlo simulation cases, with colour-coded bars transitioning from light to dark red for MCS cases 1–4 (flax/E-glass composites) and light to dark blue for MCS cases 5–8 (flax composites): (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>E</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>11</mn> </mrow> </msub> </mrow> </semantics></math> (GPa), (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>E</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> </mrow> </semantics></math> (GPa), (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>G</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>12</mn> </mrow> </msub> </mrow> </semantics></math> (GPa), (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>G</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> </mrow> </semantics></math> (GPa), (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>ν</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>12</mn> </mrow> </msub> </mrow> </semantics></math> and (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>ν</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Interface reversed cumulative surface percentages as functions of interfacial stresses: (<b>a1</b>,<b>b1</b>,<b>c1</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>a2</b>,<b>b2</b>,<b>c2</b>) <math display="inline"><semantics> <mrow> <mfenced open="|" close="|" separators="|"> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>n</mi> <mi>t</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math>, for flax/E-glass composites (MCS cases 1–4) subjected to transverse tension (<math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa), where the leftmost point represents the percentage of interface regions experiencing normalised interfacial stresses greater than 0.1, progressively decreasing rightward to illustrate the proportion subjected to increasing stress, with MCS 1 (baseline) shown by the red line, which may be partially obscured when comparing data from MCS 2, MCS 3, and MCS 4 in each subplot.</p>
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<p>Interface reversed cumulative surface percentages as functions of interfacial stresses: (<b>a1</b>,<b>b1</b>,<b>c1</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>a2</b>,<b>b2</b>,<b>c2</b>) <math display="inline"><semantics> <mrow> <mfenced open="|" close="|" separators="|"> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>n</mi> <mi>t</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math>, for flax composites (MCS cases 5–8) subjected to transverse tension (<math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mtext> </mtext> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">a</mi> <mo>)</mo> </mrow> </semantics></math>, where the leftmost point represents the percentage of interface regions experiencing normalised interfacial stresses greater than 0.1, progressively decreasing rightward to illustrate the proportion subjected to increasing stress, with MCS 5 (baseline) shown by the red line, which may be partially obscured when comparing data from MCS 6, MCS 7, and MCS 8 in each subplot.</p>
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<p>Interface reversed cumulative surface percentages as functions of interfacial stresses: (<b>a1</b>,<b>b1</b>,<b>c1</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>a2</b>,<b>b2</b>,<b>c2</b>) <math display="inline"><semantics> <mrow> <mfenced open="|" close="|" separators="|"> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>n</mi> <mi>t</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math>, for MCS cases 1–4 (flax/E-glass composites) subjected to out-of-plane shear (<math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mtext> </mtext> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">a</mi> <mo>)</mo> </mrow> </semantics></math>, where the leftmost point represents the percentage of interface regions experiencing normalised interfacial stresses greater than 0.1, progressively decreasing rightward to illustrate the proportion subjected to increasing stress, with MCS 1 (baseline) shown by the red line, which may be partially obscured when comparing data from MCS 2, MCS 3, and MCS 4 in each subplot.</p>
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<p>Interface reversed cumulative surface percentages as functions of interfacial stresses: (<b>a1</b>,<b>b1</b>,<b>c1</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>a2</b>,<b>b2</b>,<b>c2</b>) <math display="inline"><semantics> <mrow> <mfenced open="|" close="|" separators="|"> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>n</mi> <mi>t</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math>, for MCS cases 5–8 (flax laminae) subjected to out-of-plane shear (<math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mtext> </mtext> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">a</mi> <mo>)</mo> </mrow> </semantics></math>, where the leftmost point represents the percentage of interface regions experiencing normalised interfacial stresses greater than 0.1, progressively decreasing rightward to illustrate the proportion subjected to increasing stress, with MCS 5 (baseline) shown by the red line, which may be partially obscured when comparing data from MCS 6, MCS 7, and MCS 8 in each subplot.</p>
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<p>Normalised von Mises stress versus reversed cumulative matrix volume percentages for flax/E-glass composites (MCS Cases 1–4), subjected to: (<b>a1</b>,<b>b1</b>,<b>c1</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, (<b>a2</b>,<b>b2</b>,<b>c2</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>12</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, and (<b>a3</b>,<b>b3</b>,<b>c3</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, where the leftmost point represents all matrix regions (100%), progressively decreasing rightward to show the proportion subjected to increasing stress, with MCS 1 (baseline) indicated by the red line, which may be partially obscured when comparing data from MCS 2, MCS 3, and MCS 4 in each subplot.</p>
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<p>Normalised von Mises stress versus reversed cumulative matrix volume percentages for flax composites (MCS cases 5–8), subjected to: (<b>a1</b>,<b>b1</b>,<b>c1</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, (<b>a2</b>,<b>b2</b>,<b>c2</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>12</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, and (<b>a3</b>,<b>b3</b>,<b>c3</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, where the leftmost point represents all matrix regions (100%), progressively decreasing rightward to show the proportion subjected to increasing stress, with MCS 5 (baseline) indicated by the red line, which may be partially obscured when comparing data from MCS 6, MCS 7, and MCS 8 in each subplot.</p>
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<p>Average normalised <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>v</mi> <mi>M</mi> </mrow> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msubsup> </mrow> </semantics></math> calculated across eight Monte Carlo simulations under varying loading conditions, with colour-coded bars transitioning from light to dark red for MCS cases 1–4 (flax/E-glass composites) and light to dark blue for MCS cases 5–8 (flax composites): (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>11</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mtext> </mtext> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">a</mi> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mtext> </mtext> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">a</mi> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>12</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mtext> </mtext> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">a</mi> </mrow> </semantics></math> and (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mtext> </mtext> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">a</mi> </mrow> </semantics></math>.</p>
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<p>Distribution of von Mises stress within the matrix of the flax/E-glass composite (excluding fibres) with a RVE size of <math display="inline"><semantics> <mrow> <mn>580</mn> <mo>×</mo> <mn>580</mn> <mtext> </mtext> <mo>μ</mo> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>, incorporating both fibre-level variabilities, shown for four distinct loading conditions: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>11</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>12</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, and (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa.</p>
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<p>Distribution of von Mises stress fields in the flax composite (excluding fibres) with a RVE size of <math display="inline"><semantics> <mrow> <mn>580</mn> <mo>×</mo> <mn>580</mn> <mtext> </mtext> <mo>μ</mo> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>, incorporating both fibre-level variabilities, shown for four distinct loading conditions: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>11</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>22</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>12</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa, and (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mover accent="true"> <mrow> <mi>σ</mi> </mrow> <mo stretchy="false">^</mo> </mover> </mrow> <mrow> <mn>23</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> MPa.</p>
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17 pages, 3641 KiB  
Article
Study on the Influence of Laser Welding Residual Stress on the Fatigue Strength of a TC4 Thin Sheet Butt Joint
by Yingxuan Liang, Yu Liu, Yang Yu, Jun Zhou and Chongli Huang
Crystals 2025, 15(3), 230; https://doi.org/10.3390/cryst15030230 - 27 Feb 2025
Viewed by 249
Abstract
In order to further study the effect of welding residual stress on the fatigue strength of a TC4 titanium alloy sheet during laser welding, a laser welding butt joint model for TC4 titanium alloy sheets was established using ABAQUS (2022) software. The temperature [...] Read more.
In order to further study the effect of welding residual stress on the fatigue strength of a TC4 titanium alloy sheet during laser welding, a laser welding butt joint model for TC4 titanium alloy sheets was established using ABAQUS (2022) software. The temperature and residual stress fields generated during the welding process were comprehensively simulated, and the melt pool shape and residual stress magnitudes were experimentally verified. The experimental parameters included a laser power range of 900–1200 W, welding speeds of 12.5 and 25 mm/s, and a double-sided welding approach with a cooling interval of 20 s between passes. The findings indicate that welding residual stress is primarily concentrated around the weld and the heat-affected zone, predominantly as tensile stress, with the maximum value observed at the weld’s initiation point, reaching 920 MPa—close to the material’s tensile strength limit. Under ideal conditions (without considering welding residual stress), the fatigue life at the weld area is estimated to reach 188,799 cycles, while the fatigue life of the base material without welding is calculated to be 167,109 cycles. However, when accounting for welding residual stress, the fatigue strength of the sheet decreases significantly, with the minimum fatigue life occurring at the weld toe, measured at 10,471 cycles. This study demonstrates that welding residual stress has a substantial impact on the fatigue life of TC4 titanium alloy sheets, particularly in the heat-affected zone, where the fatigue life is reduced by nearly 94% compared to the ideal condition. These results provide critical insights for improving the fatigue performance of laser-welded TC4 titanium alloy components in engineering applications. Full article
(This article belongs to the Section Crystalline Metals and Alloys)
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Figure 1
<p>Welding schematic diagram.</p>
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<p>High precision X-ray residual stress nondestructive testing system.</p>
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<p>Double-ellipsoidal heat source model.</p>
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<p>Mesh model.</p>
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<p>Weld seam shape and calibration; (<b>a</b>) base metal zone; (<b>b</b>) weld zone; (<b>c</b>) heat-affected zone.</p>
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<p>Temperature field distribution at 2 s.</p>
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<p>Residual stress experimental measurement points and numerical calculation paths.</p>
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<p>Equivalent residual stress test measurements and numerical calculation results.</p>
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<p>Defects in the cross-section of the weld.</p>
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<p>Welding stress distribution in different directions (S11 and S22) at 2 s.</p>
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<p>Residual stress distribution.</p>
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<p>Fatigue life cloud.</p>
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