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15 pages, 5871 KiB  
Article
Stability and Control of Surrounding Rock of a Trapezoidal Roadway Retained with Hard Roof Cutting
by Shizhong Zhang, Chuangnan Ren, Xinyao Gao, Yongsheng Gao, Lianyi Nie, Shaodong Li and Moulie Jiang
Appl. Sci. 2025, 15(1), 348; https://doi.org/10.3390/app15010348 - 2 Jan 2025
Viewed by 248
Abstract
Hard roof top-cutting and gob-side roadway retention is an effective way to improve the panel recovery ratio and reduce ground pressure. Based on the condition of Pingmei No.2 Mine, this paper establishes a stability mechanics model for the roof in a trapezoidal top-cutting [...] Read more.
Hard roof top-cutting and gob-side roadway retention is an effective way to improve the panel recovery ratio and reduce ground pressure. Based on the condition of Pingmei No.2 Mine, this paper establishes a stability mechanics model for the roof in a trapezoidal top-cutting roadway with inclined coal seam, in order to analyze the factors influencing the stability of the roof. This paper studies the deformation characteristics and control mechanism of the surrounding rock in a trapezoidal top-cutting roadway, and proposes targeted stability control technologies for the surrounding rock. The results showed that: (1) in a trapezoidal top-cutting roadway in the hard roof with inclined coal seam, the tensile stress of the uncut roof was inversely proportional to the coal seam dip angle, roof thickness and top-cutting height, while it was proportional to the top-cutting angle. According to actual engineering conditions, the top-cutting angle and height of the roof of the 21,100-panel were determined to be 10° and 5.0 m, respectively; (2) the special structure of the trapezoidal roadway led to asymmetric stress distribution in the surrounding rock, especially in the roof and rib. Using top-cutting, the pressure relief reduced the roof stress from 6.73 MPa to 2.04 MPa, the high stress zone moved to the inside of the solid coal, and the roof slid and deformed along the top line, showing characteristics of a “large deformation on the top side”; and (3) high-strength long anchor cables were used to reinforce the roof on the cut top side. Telescopic U-shaped steel and windshield cloth were used to block gangue and prevent wind leakage in the roadway. The on-site industrial test measured the maximum subsidence of the roof at 120 mm, and the maximum layer separation was 29 mm. Relative to non-top-cutting methods, the roof and sides showed significantly reduced deformation throughout the mining operations, which verified the reliability of the control technology. Full article
(This article belongs to the Section Energy Science and Technology)
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Figure 1
<p>Layout of the 21,100 panel.</p>
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<p>Original support of the headgate.</p>
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<p>Mechanical model of the roof in the top-cutting roadway.</p>
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<p>The relationship between tensile stress and the top-cutting height and angle.</p>
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<p>The relationship between tensile stress and the coal seam dip angle, as well as the roof thickness.</p>
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<p>Numerical calculation model of a top-cutting roadway.</p>
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<p>Stress distribution and deformation characteristics of surrounding rock during excavation period: (<b>a</b>) vertical stress; (<b>b</b>) vertical displacement.</p>
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<p>Stress distribution and deformation characteristics of surrounding rock during recovery period: (<b>a</b>) vertical stress; (<b>b</b>) vertical displacement.</p>
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<p>Stress distribution and deformation characteristics of surrounding rock under the condition of top-cutting: (<b>a</b>) vertical stress; (<b>b</b>) vertical displacement.</p>
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<p>Stress transfer mechanism between surrounding rocks of roadway after top-cutting.</p>
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<p>Schematic diagram of key technologies for controlling surrounding rock of top-cutting roadway: (<b>a</b>) floor plan of gangue protection; (<b>b</b>) cross-sectional view of roof reinforcement support.</p>
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<p>Roadway deformation monitoring results and development effectiveness: (<b>a</b>) roadway deformation; (<b>b</b>) roof delamination; (<b>c</b>) roadway development effectiveness.</p>
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17 pages, 3444 KiB  
Article
Finite Element Analysis of T-Shaped Concrete-Filled Steel Tubular Short Columns with Stiffening Ribs Under Axial Compression
by Xiaosan Yin, Hongliang Yue, Yuzhou Sun, Guoyang Fu, Jimin Li and Md. Mashiur Rahman
Buildings 2025, 15(1), 112; https://doi.org/10.3390/buildings15010112 - 31 Dec 2024
Viewed by 287
Abstract
A new type of stiffening rib is proposed to improve the mechanical performance of T-shaped concrete-filled steel tubular (CFST) columns. A finite element model was established using the general-purpose commercial software ABAQUS 2022. After verification through comparison with experimental data, the developed finite [...] Read more.
A new type of stiffening rib is proposed to improve the mechanical performance of T-shaped concrete-filled steel tubular (CFST) columns. A finite element model was established using the general-purpose commercial software ABAQUS 2022. After verification through comparison with experimental data, the developed finite element model was employed to numerically evaluate the performance of T-shaped CFST short columns with stiffening ribs under axial compression. The results indicated that the new stiffening ribs are capable of significantly reducing the buckling deformation of the steel tube, enhancing the confinement effect of the steel tube on the core concrete, and improving the combined performance of the steel tube and the concrete. The thickness and material strength of the stiffening ribs had a notable impact on the ultimate bearing capacity and ductility of the short column specimens. When the thickness of the stiffening ribs increased from 5 mm to 8 mm, the ultimate bearing capacity correspondingly increased by 10.51% to 31.77%, while the ductility coefficient improved by 6.48% to 17.20%. When the steel strength increased from 262.50 MPa to 345 MPa and 390 MPa, the ultimate bearing capacity correspondingly increased by 17.36%, 19.78%, and 30.50%, and the ductility coefficient improved by 12%, 13.87% and 23.92%. The changes in the specifications and arrangement of the stiffening ribs had no significant effect on the ultimate bearing capacity and ductility of the specimens. The change in angle steel specifications caused variations in ultimate bearing capacity within ±5% and variations in the ductility coefficient within ±10%. Changes in the arrangement caused variations in ultimate bearing capacity within ±1% and variations in the ductility coefficient within ±5%. Full article
(This article belongs to the Section Building Structures)
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<p>Stress–strain curves of concrete and steel.</p>
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<p>Section form of the column specimens [<a href="#B23-buildings-15-00112" class="html-bibr">23</a>].</p>
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<p>Mesh generation.</p>
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<p>Stress contour plots of specimen 1-T300-6: (<b>a</b>) Shape of the overall column; (<b>b</b>) Face 5 buckling; (<b>c</b>) outward buckling at concave corners; (<b>d</b>) concrete at face 5.</p>
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<p>Comparison of load–longitudinal displacement curves from experimental tests and finite element simulations.</p>
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<p>Different arrangements of stiffening ribs on T-shaped concrete-filled steel tube short columns: (<b>a</b>) The first type of stiffening ribs’ arrangement; (<b>b</b>) The second type of stiffening ribs’ arrangement; (<b>c</b>) The third type of stiffening ribs’ arrangement; (<b>d</b>) The fourth type of stiffening ribs’ arrangement.</p>
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<p>Stress contour plots of specimen 4-T300-6J-A: (<b>a</b>) Shape of the overall column; (<b>b</b>) Face 5 buckling; (<b>c</b>) outward buckling at concave corners; (<b>d</b>) concrete at face 5; (<b>e</b>) concrete at concave corners.</p>
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<p>Comparison of load–longitudinal displacement curves of T-shaped CFST short columns with and without stiffening ribs under axial compression: (<b>a</b>) The wall thickness of the steel tube is 6 mm; (<b>b</b>) The wall thickness of the steel tube is 6 mm; (<b>c</b>) The wall thickness of the steel tube is 5 mm.</p>
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<p>Load–longitudinal displacement curves of the T-shaped CFST short columns with stiffening ribs: (<b>a</b>) thickness of stiffening ribs; (<b>b</b>) specifications of stiffening ribs; (<b>c</b>) strength of stiffening ribs; (<b>d</b>) arrangements of stiffening ribs.</p>
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<p>Ductility coefficient histogram.</p>
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16 pages, 4480 KiB  
Article
Evaluation of the Efficiency of Heat Exchanger Channels with Different Flow Turbulence Methods Using the Entropy Generation Minimization Criterion
by Piotr Bogusław Jasiński, Grzegorz Górecki and Zbigniew Cebulski
Energies 2025, 18(1), 132; https://doi.org/10.3390/en18010132 - 31 Dec 2024
Viewed by 251
Abstract
This paper presents the results of an optimization analysis of two types of thermal fluid channels. The selected geometries were evaluated according to the criterion of the Entropy Generation Minimization method as suggested by Adrian Bejan, with reference to a smooth pipe of [...] Read more.
This paper presents the results of an optimization analysis of two types of thermal fluid channels. The selected geometries were evaluated according to the criterion of the Entropy Generation Minimization method as suggested by Adrian Bejan, with reference to a smooth pipe of the same diameter. The aim of this research was to assess the effectiveness of two channels that intensify heat transfer in different ways: with an insert (disrupting the flow in the pipe core) and with internal fins (disrupting the flow at the pipe wall), and to compare the results using the same criterion: the EGM method. The tested insert consisted of spaced streamline-shaped flow turbulizing the elements fixed in the axis of the pipe and spaced at equal distances from each other. The second channel was formed by making a right-angled triangle (rib profile) on the deformation of the pipe wall perimeter. Using computer modeling, the effect of the two geometric parameters of the above-mentioned channels on the flux of entropy generated was studied. These are (a) the diameter of the disturbing element (“droplet”) and the distance between these elements for a channel with a turbulent insert, and (b) the height of the rib and the longitudinal distance between them for a finned channel. The novelty resulting from the research is the discovery that the turbulization of the flow in the pipe wall boundary layer generates significantly less irreversible entropy than the disturbance of the flow in the pipe axis by the insert. Full article
(This article belongs to the Collection Advances in Heat Transfer Enhancement)
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Figure 1
<p>Tube with cross ribs: (<b>a</b>) 3D view, (<b>b</b>) comparison of rib sizes, and (<b>c</b>) tested rib heights.</p>
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<p>Turbulizing insert: (<b>a</b>) 3D view, (<b>b</b>) comparison of the size of the “droplets”, and (<b>c</b>) dimensions of the diameters of the tested elements.</p>
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<p>Mutual proportions of insertion-disturbing elements.</p>
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<p>Diagram of variable designations for Equation (2) in the smooth pipe elementary section.</p>
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<p>The relative entropy generation for forced convection heat transfer in a smooth tube [<a href="#B1-energies-18-00132" class="html-bibr">1</a>].</p>
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<p>Repetitive and periodic segments of the tested pipes as computational domains.</p>
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<p>Repeated and periodic segment of the pipes under study. Heat transfer diagram in the computational domain.</p>
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<p>Total entropy generation rate for dimensionless longitudinal distance <span class="html-italic">L</span>/<span class="html-italic">D</span> = 0.77: (<b>a</b>) pipe with insert and (<b>b</b>) ribbed pipe.</p>
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<p>Relative entropy generation rate for dimensionless longitudinal distance <span class="html-italic">L</span>/<span class="html-italic">D</span> = 0.77: (<b>a</b>) pipe with insert and (<b>b</b>) ribbed pipe.</p>
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<p>Total entropy generation rate for dimensionless longitudinal distance L/D = 1.38: (<b>a</b>) pipe with insert and (<b>b</b>) ribbed pipe.</p>
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<p>Relative entropy generation rate for dimensionless longitudinal distance L/D = 1.38: (<b>a</b>) pipe with insert and (<b>b</b>) ribbed pipe.</p>
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<p>Total entropy generation rate for dimensionless longitudinal distance L/D = 3.27: (<b>a</b>) pipe with insert and (<b>b</b>) ribbed pipe.</p>
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<p>Relative entropy generation rate for dimensionless longitudinal distance L/D = 3.27: (<b>a</b>) pipe with insert and (<b>b</b>) ribbed pipe.</p>
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<p>Velocity vector map for the two chosen longitudinal distances with marked turbulence zones: <span class="html-italic">L</span>/<span class="html-italic">D</span> = 0.92 and <span class="html-italic">L</span>/<span class="html-italic">D</span> = 1.85, (<b>a</b>) ribbed pipe, and (<b>b</b>) pipe with insert.</p>
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32 pages, 58063 KiB  
Article
Study on Flow Structure Characteristics Along the Latticework Duct Subchannels and Classification Boundary Prediction
by Minlong Li, Huishe Wang, Ke Yang, Rongguo Yu and Jingze Ton
Aerospace 2025, 12(1), 22; https://doi.org/10.3390/aerospace12010022 (registering DOI) - 31 Dec 2024
Viewed by 290
Abstract
To reasonably divide the types of flow units along the latticework subchannel, one must prepare for the establishment of a one-dimensional fluid network model of the latticework in the middle region of the turbine blade. The characteristics of the flow structure along the [...] Read more.
To reasonably divide the types of flow units along the latticework subchannel, one must prepare for the establishment of a one-dimensional fluid network model of the latticework in the middle region of the turbine blade. The characteristics of the flow structure along the latticework subchannel were studied by numerical simulation. The effects of rib angle (15–45°), the ratio of rib width to rib spacing (0.3–1.0), and inlet Reynolds umber (21,000–80,000) on the flow structure along the subchannel are summarized. The results indicated that the ratio of rib width to rib spacing and inlet Reynolds number had no effect on the distribution position of each flow unit in the subchannel. The change of rib angle did not change the flow structure type along the subchannel. The longitudinal vortex was mainly formed by one turning vortex and two detached vortices. The narrowing of the turning channel will cause the turning vortex to induce a secondary longitudinal vortex. There were five kinds of flow structures along the subchannel: transverse vortex zone (entrance of the inlet section), uniform flow zone (inlet section), longitudinal vortex generation zone (turning channel section), longitudinal vortex zone (turning channel section), and longitudinal vortex free development zone (outlet section). This finding provides support for the selection of empirical formulas for each module in the one-dimensional modeling of subchannels. Finally, the boundary prediction equations of each flow structure in the subchannel were established, and the average prediction error was less than 10%. The rationality of the flow structure division along the latticework subchannel was improved, and the modeling efficiency of the latticework one-dimensional model was optimized. Full article
(This article belongs to the Section Aeronautics)
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<p>Gas turbine latticework turbine blade [<a href="#B16-aerospace-12-00022" class="html-bibr">16</a>].</p>
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<p>Geometric model and important parameters of the latticework channel.</p>
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<p>Iteration residual curve of the numerical calculation process.</p>
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<p>Latticework mesh division diagram.</p>
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<p>Yplus contours of the latticework wall.</p>
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<p>Subchannel wall relative Nusselt number diagram.</p>
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<p>Latticework flow resistance coefficients under different turbulence models.</p>
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<p>k-ω SST model and experimental heat transfer distribution diagram.</p>
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<p>Latticework subchannel number and parameter cross-section (<span class="html-italic">t</span>/<span class="html-italic">w</span> = 0.3, <span class="html-italic">β</span> = 45°).</p>
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<p>The streamline velocity contours along the subchannel.</p>
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<p><span class="html-italic">t</span>/<span class="html-italic">w</span> = 0.3, <span class="html-italic">β</span> = 45° latticework subchannel mass flow distribution characteristics.</p>
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<p>Distribution of characteristic parameters along the latticework subchannel.</p>
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<p>Distribution of characteristic parameters along the latticework subchannel.</p>
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<p><span class="html-italic">t</span>/<span class="html-italic">w</span> = 0.3, <span class="html-italic">β</span> = 30°, the distribution of characteristic parameters along the subchannel.</p>
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<p><span class="html-italic">t</span>/<span class="html-italic">w</span> = 0.3, <span class="html-italic">β</span> = 30°, the contours of characteristic parameters along the subchannel.</p>
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<p><span class="html-italic">t</span>/<span class="html-italic">w</span> = 0.3, <span class="html-italic">β</span> = 45°, latticework rib subchannel (Channel 5) characteristic parameters.</p>
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<p>Diagram of flow unit type along latticework subchannels (<span class="html-italic">t</span>/<span class="html-italic">w</span> = 0.3, <span class="html-italic">β</span> = 45°).</p>
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<p>Transverse vorticity velocity contours at the entrance of the subchannel inlet region.</p>
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<p>Distribution curve of velocity and velocity component variation.</p>
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<p>Parameter prediction distribution.</p>
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<p>Average reattachment length prediction error analysis.</p>
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<p>Prediction equation transformation method.</p>
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<p>Change rule of average reattachment length.</p>
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<p>Contours of the average reattachment length change rule.</p>
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<p>Separation distance prediction error analysis.</p>
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<p>Contours of the separation distance change rule.</p>
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<p>Transverse vorticity velocity contours at the entrance of the turning channel.</p>
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<p>Vortex velocity contours at the exit of the turning channel.</p>
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<p>Simplified flow process of the turning channel.</p>
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<p>Vortex velocity contours of the narrow turning channel.</p>
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<p>Vortex velocity contours of the turning channel with a larger rib angle.</p>
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<p>Simplified model of the entrance and exit of the turning channel.</p>
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<p>Error analysis of the turning channel prediction model.</p>
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<p>Distribution contours of the entrance and exit boundaries of the turning channel.</p>
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14 pages, 5551 KiB  
Article
Surgical Treatment of Early-Onset Scoliosis: Traditional Growing Rod vs. Magnetically Controlled Growing Rod vs. Vertical Expandable Prosthesis Titanium Ribs
by Bruna Maccaferri, Francesco Vommaro, Chiara Cini, Giuseppe Filardo, Luca Boriani and Alessandro Gasbarrini
J. Clin. Med. 2025, 14(1), 177; https://doi.org/10.3390/jcm14010177 - 31 Dec 2024
Viewed by 226
Abstract
Objectives: Severe early-onset scoliosis (EOS) can be addressed by different growth-friendly approaches, although the indications of each technique remain controversial. The aim of this study was to compare, in a large series of patients, the potential and limitations of the different distraction-based surgical [...] Read more.
Objectives: Severe early-onset scoliosis (EOS) can be addressed by different growth-friendly approaches, although the indications of each technique remain controversial. The aim of this study was to compare, in a large series of patients, the potential and limitations of the different distraction-based surgical techniques to establish the most suitable surgical approach to treat EOS. Methods: We conducted a retrospective observational cohort study evaluating 62 EOS cases treated between January 2002 and December 2021 with a traditional growing rod (TGR), a magnetically controlled growing rod (MCGR) and vertical expandable prosthesis titanium ribs (VEPTR) at IRCSS Istituto Ortopedico Rizzoli, Bologna, Italy. The patients included had a mean age of 7 years and a mean follow-up of 36 months. The COBB angle was measured on x-rays at preoperative, early postoperative, and end of follow-up, and complications were recorded. Results: in our cohort, VEPTR was mainly used in congenital scoliosis (50% vs. a mean value of 25.8%) and syndromic scoliosis (42.9% vs. a mean value of 25.8%). MCGR was mainly used in idiopathic scoliosis (73.9% vs. an average value of 41.9%). TGR was mostly used in muscular neurology EOS (16% vs. an average value of 6.5%). The collected data show a similar deformity correction rate in growing-rod implants in VEPTR, TGR, and MCGR. The mean curve reduction was 25.8 95% CI (21.8–29.8) (p < 0.0005). Compared with preoperative measurements, significant differences in curve magnitude correction between subgroups occurred at the final treatment measurements, when patients with MCGR had a significantly larger correction (53.2° ± 20.84 in %33.9 con DS ± 14.27) than VEPTR (27.12°± 19.13 in %19.7° ± 13.7). Conclusions: Different growing-rod techniques are applied based on EOS etiology. While all EOS etiologies benefited from this surgical approach, congenital EOS had poorer results. Overall, MCGR has been the preferred option for idiopathic EOS and appears to be the most effective in correcting the primary curve. Full article
(This article belongs to the Section Orthopedics)
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<p>Graphic representation of an example of traditional growing rods (TGR).</p>
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<p>X-rays of early onset scoliosis (EOS) corrected with traditional growing rods (TGR): (<b>A</b>) pre-operative antero-posterior X-ray view; (<b>B</b>) post-operative antero-posterior X-ray view; (<b>C</b>) pre-operative lateral X-ray view; (<b>D</b>) post-operative lateral X-ray view.</p>
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<p>X-rays of early onset scoliosis (EOS) corrected with traditional growing rods (TGR): (<b>A</b>) pre-operative antero-posterior X-ray view; (<b>B</b>) post-operative antero-posterior X-ray view; (<b>C</b>) pre-operative lateral X-ray view; (<b>D</b>) post-operative lateral X-ray view.</p>
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<p>Graphic representation of an example of magnetically controlled growing rods (MCGR).</p>
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<p>X-Rays of early onset scoliosis (EOS) corrected with magnetically controlled growing rods (MCGR): (<b>A</b>) pre-operative antero-posterior X-ray view; (<b>B</b>) post-operative antero-posterior X-ray view; (<b>C</b>) pre-operative lateral X-ray view; (<b>D</b>) post-operative lateral X-ray view.</p>
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<p>X-Rays of early onset scoliosis (EOS) corrected with magnetically controlled growing rods (MCGR): (<b>A</b>) pre-operative antero-posterior X-ray view; (<b>B</b>) post-operative antero-posterior X-ray view; (<b>C</b>) pre-operative lateral X-ray view; (<b>D</b>) post-operative lateral X-ray view.</p>
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<p>Graphic representation of an example of vertical expandable prosthetic titanium rib (VEPTR).</p>
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<p>X-rays of early onset scoliosis (EOS) corrected with vertical expandable prosthetic titanium rib (VEPTR): (<b>A</b>) pre-operative antero-posterior X-ray view; (<b>B</b>) post-operative antero-posterior X-ray view; (<b>C</b>) pre-operative lateral X-ray view; (<b>D</b>) post-operative lateral X-ray view.</p>
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<p>X-rays of early onset scoliosis (EOS) corrected with vertical expandable prosthetic titanium rib (VEPTR): (<b>A</b>) pre-operative antero-posterior X-ray view; (<b>B</b>) post-operative antero-posterior X-ray view; (<b>C</b>) pre-operative lateral X-ray view; (<b>D</b>) post-operative lateral X-ray view.</p>
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22 pages, 9855 KiB  
Article
Predictive Control for Steel Rib Bending Based on Deep Learning
by Yijiang Xia, Jinhui Luo, Zhuolin Ou, Xin Han, Junlin Deng and Ning Wu
J. Mar. Sci. Eng. 2025, 13(1), 41; https://doi.org/10.3390/jmse13010041 - 30 Dec 2024
Viewed by 284
Abstract
In the shipbuilding industry, the inefficiency of the successive approximation control method in CNC cold-bending machines has hindered productivity in steel bending manufacturing, particularly for rib profiles. This study proposes control methods for cold bending machines based on deep learning models to address [...] Read more.
In the shipbuilding industry, the inefficiency of the successive approximation control method in CNC cold-bending machines has hindered productivity in steel bending manufacturing, particularly for rib profiles. This study proposes control methods for cold bending machines based on deep learning models to address this challenge, including CNN and Transformer-CNN (T-CNN), to predict the elastic spring-back rate of cold-processed metal profiles and generate precise control pulses for achieving target bending angles. Experimental validation using real-world datasets collected from a shipyard’s CNC cold bending machine demonstrates that the T-CNN model significantly reduces the number of steps required for each bending operation, achieving a 75% reduction in production time and substantially enhancing processing efficiency. By leveraging the strengths of CNNs and Transformer architectures, the T-CNN model excels at handling long sequence data and capturing global dataset characteristics. Results show that the T-CNN model outperforms traditional control methods and standard CNNs in prediction accuracy, stability, and efficiency, making it a superior choice for cold bending control. Full article
(This article belongs to the Section Ocean Engineering)
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Figure 1
<p>The control scheme of steel bending with the successive approximation control method.</p>
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<p>Control flowchart of the rib bending with the successive approximation control method.</p>
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<p>The bending machine with a rib workpiece.</p>
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<p>Schematic diagram of the secant line measurement control method for bending a rib with a curve of <math display="inline"><semantics> <mrow> <mi>f</mi> <mfenced> <mi>x</mi> </mfenced> </mrow> </semantics></math> [<a href="#B31-jmse-13-00041" class="html-bibr">31</a>].</p>
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<p>Rib-bending control flowchart with a deep learning model.</p>
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<p>The predictive control scheme of a deep learning model implemented in the successive ap-proximation control loop.</p>
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<p>The structure of the proposed CNN model.</p>
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<p>The structure of the T-CNN and the transformer part is highlighted within the dashed rectangle.</p>
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<p>Bulb flat steel-bending process.</p>
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<p>Part of the recorded bending angle data.</p>
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<p>The loss values of the training and validation of the trained CNN.</p>
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<p>The loss values of the training and validation of the trained T-CNN.</p>
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<p>Comparison of the true and predicted values with the CNN.</p>
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<p>Comparison of the true and predicted values with the T-CNN.</p>
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<p>Distribution of true and predicted values of the CNN.</p>
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<p>Distribution of true and predicted values of the T-CNN.</p>
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<p>Residual distribution of true and predicted values by the CNN.</p>
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<p>Residual distribution of true and predicted values by the T-CNN.</p>
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<p>The prediction performance for the bending angle pulses with the CNN.</p>
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<p>The prediction performance for the bending angle pulses with the T-CNN.</p>
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12 pages, 1901 KiB  
Article
A Feasibility Study of a Controlled Standing Fulcrum Side-Bending Test in Adolescent Idiopathic Scoliosis
by Christian Wong, Christos Koutras, Hamed Shayestehpour, Benny Dahl, Miguel A. Otaduya and John Rasmussen
J. Clin. Med. 2024, 13(24), 7809; https://doi.org/10.3390/jcm13247809 - 20 Dec 2024
Viewed by 312
Abstract
Background/Objectives: Spinal flexibility radiographs are important in adolescent idiopathic scoliosis (AIS) for clinical decision-making. In this study, we introduce a new method, the ‘quantitatively controlled standing fulcrum side-bending’ test (CSFS test). This is a feasibility study; we aimed to quantify the applied [...] Read more.
Background/Objectives: Spinal flexibility radiographs are important in adolescent idiopathic scoliosis (AIS) for clinical decision-making. In this study, we introduce a new method, the ‘quantitatively controlled standing fulcrum side-bending’ test (CSFS test). This is a feasibility study; we aimed to quantify the applied force and track the temporospatial changes in the spine specifically by measuring the continuous change in the Cobb angle (in degrees) during lateral bending. Methods: In this cross-sectional study, we included patients with AIS. Using a low-dose cinematic fluoroscopic technique, we captured the lateral bending of the thoracolumbar vertebral spine while inducing quantified lateral force on the ribs by a force gauge in a three-point fixation setup of controlled lateral bending. Trial registration number: H-1703423. Results: Twenty-one patients with small-curve AIS were included as subjects. All subjects performed the CSFS test adequately. They had small curves with a mean Cobb angle of 12.0 (range: 0.0–26.0, SD: 7.1). The measured median stiffness was 3.66 N/degrees (°) of the Cobb angle (range: 0.02–11.81) with a median coefficient of determination R2 of 0.58 (range: 0.002–0.92) by regression analyses. When analysed concerning the median-term clinical outcome of either progression/regression or stationary curves, various Cobb angle measurements and the other experimental parameters, there were no significant relationships. Conclusions: The CSFS test is feasible to quantify the force applied and the temporospatial changes in the spine during lateral bending. The CSFS test has been utilised in basic research for mechanical characterisation of the scoliotic spine and has the potential of being implemented directly in patient-specific bracing to estimate the forces needed for brace correction and adjustment so as not to supersede the allowed skin pressure. Full article
(This article belongs to the Special Issue Optimizing Outcomes in Scoliosis and Complex Spinal Surgery)
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<p>Timeline of the history of the subject’s participation; subjects were included in a study performing EMG and electric stimulation (*). In the interim, we closed this study, and 21 of the 45 subjects with AIS performed controlled lateral bending at the next clinical follow-up.</p>
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<p>(<b>a</b>). Photographs and schematic depiction of the experimental force-and-deformation acquisition setup (top). We capture the low-dose radiographs of the subject’s torso while simultaneously increasing a controlled force (F3) on the ribs. This force was balanced by a force on the opposite shoulder (F1) obtained by resting the shoulder against a wall attached to the X-ray bed (see top-left inset) and a force on the pelvis (F2) produced by a fixing belt (see bottom-left inset). The three forces together resemble the three-point pressure principle of common scoliosis braces. Using force and torque equilibrium conditions, together with body measurements, we estimate the reaction forces on the shoulder and the pelvis. (<b>b</b>). Radiographs of a subject with force application from the two directions (from left to right) (below).</p>
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<p>Examples of time series of the applied force, the Cobb angles (<b>a</b>), and the resulting stiffness assessments and correlations (<b>b</b>). Blue colour designates force from the right-hand side, and red is from the left-hand side.</p>
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<p>Stiffnesses for individual subjects with median in the N/degree and the 10th and 90th percentiles—right (blue bar) and stiffness—left (red bar). X-axis with subject numbers.</p>
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16 pages, 5893 KiB  
Article
Development of Rehabilitation Glove: Soft Robot Approach
by Tomislav Bazina, Marko Kladarić, Ervin Kamenar and Goran Gregov
Actuators 2024, 13(12), 472; https://doi.org/10.3390/act13120472 - 22 Nov 2024
Viewed by 577
Abstract
This study describes the design, simulation, and development process of a rehabilitation glove driven by soft pneumatic actuators. A new, innovative finger soft actuator design has been developed through detailed kinematic and workspace analysis of anatomical fingers and their actuators. The actuator design [...] Read more.
This study describes the design, simulation, and development process of a rehabilitation glove driven by soft pneumatic actuators. A new, innovative finger soft actuator design has been developed through detailed kinematic and workspace analysis of anatomical fingers and their actuators. The actuator design combines cylindrical and ribbed geometries with a reinforcing element—a thicker, less extensible structure—resulting in an asymmetric cylindrical bellow actuator driven by positive pressure. The performance of the newly designed actuator for the rehabilitation glove was validated through numerical simulation in open-source software. The simulation results indicate actuators’ compatibility with human finger trajectories. Additionally, a rehabilitation glove was 3D-printed from soft materials, and the actuator’s flexibility and airtightness were analyzed across different wall thicknesses. The 0.8 mm wall thickness and thermoplastic polyurethane (TPU) material were chosen for the final design. Experiments confirmed a strong linear relationship between bending angle and pressure variations, as well as joint elongation and pressure changes. Next, pseudo-rigid kinematic models were developed for the index and little finger soft actuators, based solely on pressure and link lengths. The workspace of the soft actuator, derived through forward kinematics, was visually compared to that of the anatomical finger and experimentally recorded data. Finally, an ergonomic assessment of the complete rehabilitation glove in interaction with the human hand was conducted. Full article
(This article belongs to the Special Issue Modelling and Motion Control of Soft Robots)
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<p>The process of design, development, and experimental assessment of the rehabilitation glove: (<b>A</b>) circular grasping example; (<b>B</b>) finger ROM; (<b>C</b>) finger kinematics; (<b>D</b>) tuning of construction parameters in the design process; (<b>E</b>) final 3D model; (<b>F</b>) SOFA simulation; (<b>G</b>) 3D-printed segments made from TPU, featuring varying dimensions and wall thicknesses for design analysis; (<b>H</b>) experimental assessment and validation of the soft robot’s ROM; and (<b>I</b>) the developed rehabilitation glove fitted onto the user’s hand.</p>
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<p>Kinematic analysis: (<b>a</b>) workspace of the index finger in FE plane with finger joint (MCP, PIP, DIP, TIP) trajectories during circular grasping according to [<a href="#B16-actuators-13-00472" class="html-bibr">16</a>] and (<b>b</b>) soft finger actuator kinematic chain with modified DH approach. The diagram displays revolute and prismatic joints along the robot’s segments, with symbols indicating points of rotation (POP), revolute joints, and prismatic joints. Each joint is labeled with corresponding DH parameters, including joint angle (<span class="html-italic">θ<sub>i</sub></span>) and elongation (Δ<span class="html-italic">d<sub>i</sub></span>).</p>
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<p>A 3D model of the rehabilitation glove: (<b>a</b>) cross-sectional view of a single actuating element; (<b>b</b>) finger actuator composed of three segments; (<b>c</b>) cross-sectional view of cylindrical channels for compressed air supply; and (<b>d</b>) assembly of the 3D model of the rehabilitation glove.</p>
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<p>Soft actuator simulation: (<b>a</b>) volumetric mesh, (<b>b</b>) index finger simulation at 0 bar pressure (initial position), and (<b>c</b>) index finger simulation at 8 bar pressure.</p>
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<p>Soft-robotic glove fitted to the user’s hand: (<b>a</b>) all soft actuators in initial position and (<b>b</b>) all soft actuators activated.</p>
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<p>Laboratory experiments demonstrating angular motion of soft actuators under varying pressure levels (0, 2, 4, and 7 bar): (<b>a</b>) soft actuators for the index finger with overlaid kinematic representation for <span class="html-italic">p</span> = 0 bar and (<b>b</b>) soft actuators for the little finger.</p>
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<p>Experimentally obtained linear joint constraints for index and little finger depending on pressure (95% confidence intervals colored in gray): (<b>a</b>) revolute joint angle and (<b>b</b>) link offset vs. pressure.</p>
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<p>The workspace in the FE plane for: (<b>a</b>) I-finger soft actuator and (<b>b</b>) L-finger soft actuator. Eight different kinematic positions corresponding to the experimental pressures have been additionally indicated.</p>
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22 pages, 5596 KiB  
Article
Design and Rapid Prototyping of Deformable Rotors for Amphibious Navigation in Water and Air
by Chengrong Du and Dongbiao Zhao
Machines 2024, 12(12), 837; https://doi.org/10.3390/machines12120837 - 22 Nov 2024
Viewed by 498
Abstract
This paper aims to report the design of a mechanism to drive a propeller to deform between an aerial and one aquatic shape. This mechanism can realize the deformation of blade angle, radius, blade twist angle distribution and blade section thickness. Inspired by [...] Read more.
This paper aims to report the design of a mechanism to drive a propeller to deform between an aerial and one aquatic shape. This mechanism can realize the deformation of blade angle, radius, blade twist angle distribution and blade section thickness. Inspired by the Kresling origami structure and utilizing its rotation-folding motion characteristics, a propeller hub structure with variable blade angle is designed. A blade deformation unit (S-unit) with extensional-torsional kinematic characteristics is designed through the motion analysis of a spherical four-bar mechanism. A rib support structure fixed to the linkages of the s-unit is designed to achieve the change in blade section thickness. Based on motion analysis, the coordinate transformation method has been used to establish the relationship between propeller shape and deformation mechanism. The deformation of blade extension, blade twist distribution, and blade section thickness are analyzed. The deformation ability of the proposed structure can be verified then by kinematic simulation and rapid prototyping based on 3-D printing. It is proved that the proposed mechanism is applicable to deformable propeller design. The rapid prototype testing validates the stable motion of the mechanism. However, due to the relatively large self-weight of the structure, the blade has a slight deformation. In the subsequent work, the structural strength issue needs to be emphasized. Full article
(This article belongs to the Section Machine Design and Theory)
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<p>Mechanism schematics of Kresling origami and modified Kresling origami. (<b>a</b>) Kresling origami (<b>b</b>) modified Kresling origami.</p>
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<p>Geometric schematic of the Kresling structure.</p>
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<p>Mechanism schematics of spherical 4-bar mechanism. (<b>a</b>) 3-D geometrical model schematic. (<b>b</b>) Mechanism brief schematics.</p>
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<p>Mechanism schematic of the propeller hub.</p>
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<p>Mechanism schematics of a Kresling hub. (<b>a</b>) Hub shape a, (<b>b</b>) hub shape b, (<b>c</b>) hub shape c, and (<b>d</b>) hub shape d.</p>
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<p>Mechanism schematic of serial connected s-units.</p>
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<p>Schematic diagram of serial connected s-units deformation. (<b>a</b>) top view of aerial shape. (<b>b</b>) side view of aerial shape. (<b>c</b>) top view of aquatic shape. (<b>d</b>) side view of aquatic shape.</p>
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<p>Schematic diagram of blade section deformation. (<b>a</b>) Aerial shape. (<b>b</b>) Aquatic shape.</p>
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<p>Schematic diagram of deformation driving mechanism.</p>
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<p>Deformation of the deformation driving mechanism. (<b>a</b>) Top view of aerial shape. (<b>b</b>) Side view of aerial shape. (<b>c</b>) Top view of aquatic shape. (<b>d</b>) Side view of aquatic shape.</p>
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<p>Schematic diagram of coordinate system.</p>
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<p>Data graph of extensional ratio.</p>
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<p>Schematic diagram of torsional deformation.</p>
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<p>Data graph of torsional deformation.</p>
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<p>Schematic diagram of thickness variation.</p>
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<p>Schematic diagram of design specifications.</p>
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<p>Schematic diagram of the layout of drive points.</p>
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<p>Mechanism shape of different <math display="inline"><semantics> <msub> <mi>θ</mi> <mi>s</mi> </msub> </semantics></math>. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>57.377</mn> </mrow> </semantics></math>. (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>85.823</mn> </mrow> </semantics></math>. (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>96.235</mn> </mrow> </semantics></math>. (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>107.142</mn> </mrow> </semantics></math>. (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>118.312</mn> </mrow> </semantics></math>. (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>130.298</mn> </mrow> </semantics></math>.</p>
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<p>Data graph of attack angle distribution.</p>
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<p>Data comparison chart of extension ratio.</p>
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<p>Data comparison chart of attack angle distribution.</p>
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<p>Mechanism shape of different <math display="inline"><semantics> <msub> <mi>θ</mi> <mi>s</mi> </msub> </semantics></math>. (<b>a</b>) Aerial shape mesh structure. (<b>b</b>) Aquatic shape mesh structure.</p>
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<p>Stress distribution diagram. (<b>a</b>) Aerial shape stress distribution. (<b>b</b>) Aquatic shape stress distribution.</p>
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<p>Parts of propeller morphing mechanism. (<b>a</b>) Parts of equilateral unit BC linkage and oblique symmetric unit AD linkage. (<b>b</b>) Parts of equilateral unit DC linkage and oblique symmetric unit AB linkage. (<b>c</b>) Parts of upper half rib structure. (<b>d</b>) Parts of lower half rib structure.</p>
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<p>Propeller morphing mechanism. (<b>a</b>) Aerial shape of the mechanism. (<b>b</b>) Aquatic shape of the mechanism.</p>
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21 pages, 6612 KiB  
Article
Aircraft Structural Stress Prediction Based on Multilayer Perceptron Neural Network
by Wendi Jia and Quanlong Chen
Appl. Sci. 2024, 14(21), 9995; https://doi.org/10.3390/app14219995 - 1 Nov 2024
Viewed by 765
Abstract
In the field of aeronautics, aircraft, as a critical aviation tool, exert a decisive influence on the structural integrity and safety of the entire system. Accurate prediction of the stress field distribution and variations within the aircraft structure is of great importance to [...] Read more.
In the field of aeronautics, aircraft, as a critical aviation tool, exert a decisive influence on the structural integrity and safety of the entire system. Accurate prediction of the stress field distribution and variations within the aircraft structure is of great importance to ensuring its safety performance. To facilitate such predictions, a rapid assessment method for stress fields based on a multilayer perceptron (MLP) neural network is proposed. Compared to the traditional machine learning algorithm, the random forest algorithm, MLP demonstrates superior accuracy and computational efficiency in stress field prediction, particularly exhibiting enhanced adaptability when handling high-dimensional input data. This method is applied to predict stresses in the wing rib structure. By performing finite element meshing on the wing ribs, the angle of attack, inflow velocity, and node coordinates are utilized as input tensors for the model, enabling it to learn the stress distribution in the wing ribs. Additionally, a peak stress prediction model is separately established for regions experiencing peak stresses. The results indicate that the MAPE of the stress field prediction model is within 5%, with a coefficient of determination R2 exceeding 0.994. For the peak stress model, the MAPE is within 2%, with an R2 exceeding 0.995. This method offers faster computation and greater flexibility, presenting a novel approach for structural strength assessment. Full article
(This article belongs to the Section Aerospace Science and Engineering)
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<p>Data Preparation and Model Workflow.</p>
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<p>Structural FEM Model of the Wing.</p>
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<p>Simulation Stress Contours at Various Angles of Attack and Inflow Velocities.</p>
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<p>Simulation Stress Contours at Various Angles of Attack and Inflow Velocities.</p>
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<p>Nodal stress vs. angle of attack and inflow velocity at node No. 18428.</p>
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<p>Training and Validation Loss Curves for MLP Model.</p>
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<p>Stress Prediction Results for Typical Operating Conditions. (<b>a</b>) Angle of Attack: 5°; inflow Velocity: 165 km/h, (<b>b</b>) Angle of Attack: 10°; inflow Velocity: 240 km/h, (<b>c</b>) Angle of Attack: 5°; inflow Velocity: 165 km/h, (<b>d</b>) Angle of Attack: 10°; inflow Velocity: 240 km/h.</p>
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<p>Stress Prediction Results for Typical Operating Conditions. (<b>a</b>) Angle of Attack: 5°; inflow Velocity: 165 km/h, (<b>b</b>) Angle of Attack: 10°; inflow Velocity: 240 km/h, (<b>c</b>) Angle of Attack: 5°; inflow Velocity: 165 km/h, (<b>d</b>) Angle of Attack: 10°; inflow Velocity: 240 km/h.</p>
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<p>Scatter Plot of Stress Prediction by MLP Model and RF Model. (<b>a</b>) MLP Model Prediction Results; (<b>b</b>) RF Model Prediction Results.</p>
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<p>Absolute Error Distribution for Stress Prediction. (<b>a</b>) Absolute Error Distribution for Validation and Test Sets in MLP Model; (<b>b</b>) Absolute Error Distribution for Validation and Test Sets in RF Model.</p>
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<p>Peak Stress Prediction Results for MLP Model on Validation and Test Sets. (<b>a</b>) Comparison of Peak Stress Predictions Using MLP; (<b>b</b>) Stress Peak Regression Analysis.</p>
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<p>Peak Stress Prediction Results for MLP Model on Validation and Test Sets. (<b>a</b>) Comparison of Peak Stress Predictions Using MLP; (<b>b</b>) Stress Peak Regression Analysis.</p>
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<p>Areas of Equivalent Stress Concentration.</p>
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<p>Prediction Results for Nodes 18,403, 35,182, and 35,207.</p>
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<p>Prediction Results for Nodes 18,403, 35,182, and 35,207.</p>
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21 pages, 6291 KiB  
Article
Premixed Combustion Characteristics of Hydrogen/Air in a Micro-Cylindrical Combustor with Double Ribs
by Yi Ma, Wenhua Yuan, Shaomin Zhao and Hongru Fang
Energies 2024, 17(20), 5165; https://doi.org/10.3390/en17205165 - 17 Oct 2024
Viewed by 683
Abstract
Hydrogen is a promising zero-carbon fuel, and its application in the micro-combustor can promote carbon reduction. The structural design of micro-combustors is crucial for combustion characteristics and thermal performance improvement. This study investigates the premixed combustion characteristics of hydrogen/air in a micro-cylindrical combustor [...] Read more.
Hydrogen is a promising zero-carbon fuel, and its application in the micro-combustor can promote carbon reduction. The structural design of micro-combustors is crucial for combustion characteristics and thermal performance improvement. This study investigates the premixed combustion characteristics of hydrogen/air in a micro-cylindrical combustor with double ribs, using an orthogonal design method to assess the impact of various geometric parameters on thermal performance. The results indicate that the impact of rib height, rib position, and inclined angle is greater than rib width and their interactions, while their influence decreases in that order. Increased rib height improves mean wall temperature and exergy efficiency due to an expanded recirculation region and increased flame–wall contact, but negatively affects temperature uniformity and combustion efficiency. Although double ribs enhance performance, placing them too close may reduce heat transfer due to the low-temperature region between the ribs. When the double ribs are positioned at the axial third equinoxes of the micro-combustor, the highest mean wall temperature is achieved. Meanwhile, with a rib height of 0.3 and an inclined angle of 45°, the micro-combustor achieves optimal thermal performance, with the mean wall temperature increasing by 61.32 K. Full article
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<p>Schematic diagram of the micro-cylindrical combustor with double ribs.</p>
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<p>Grid-independent study for five mesh systems.</p>
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<p>Comparison between present simulation results with reported simulation and experimental results.</p>
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<p>Mean wall temperature and its nonuniformity coefficient at various <span class="html-italic">r</span> values: (<b>a</b>) Mean wall temperature at various <span class="html-italic">r</span> values; (<b>b</b>) Nonuniformity coefficient of mean wall temperature at various <span class="html-italic">r</span> values.</p>
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<p>Outer wall temperature distribution at various <span class="html-italic">r</span> values.</p>
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<p>Distribution of temperature inside the micro-combustor and at the symmetry plane under various <span class="html-italic">r</span> values at the double-rib positions of 3/9 and 5/9.</p>
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<p>Outlet mass fraction of H<sub>2</sub> at various <span class="html-italic">r</span> values.</p>
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<p>Exergy efficiency at various <span class="html-italic">r</span> values.</p>
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<p>Mean wall temperature increase and its nonuniformity coefficient decrease compared with Case0 at various <span class="html-italic">l</span><sub>1</sub> and <span class="html-italic">l</span><sub>2</sub> values: (<b>a</b>) Mean wall temperature increase compared with Case0 at various <span class="html-italic">l</span><sub>1</sub> and <span class="html-italic">l</span><sub>2</sub> values; (<b>b</b>) Nonuniformity coefficient of mean wall temperature decrease compared with Case0 at various <span class="html-italic">l</span><sub>1</sub> and <span class="html-italic">l</span><sub>2</sub> values.</p>
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<p>Mean wall temperature and outer wall temperature distribution under various distances between double ribs at the first rib position of <span class="html-italic">l</span><sub>1</sub> = 3/9 for (<b>a</b>,<b>c</b>) and <span class="html-italic">l</span><sub>1</sub> = 4/9 for (<b>b</b>,<b>d</b>).</p>
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<p>Mean wall temperature under various distances between double ribs at <span class="html-italic">l</span><sub>1</sub> = 3/9, <span class="html-italic">r</span> = 0.2, 0.3, and 0.4.</p>
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<p>Mass fraction increase of H<sub>2</sub> at the outlet compared with Case 0 under various <span class="html-italic">l</span><sub>1</sub> and <span class="html-italic">l</span><sub>2</sub> values.</p>
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<p>(<b>a</b>) Exergy efficiency increases and (<b>b</b>) outlet enthalpy decreases compared with Case 0 at various <span class="html-italic">l</span><sub>1</sub> and <span class="html-italic">l</span><sub>2</sub> values.</p>
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<p>Mean wall temperature and its nonuniformity coefficient at various <span class="html-italic">α</span> values: (<b>a</b>) Mean wall temperature at various <span class="html-italic">α</span> values; (<b>b</b>) Nonuniformity coefficient of mean wall temperature at various <span class="html-italic">α</span> values.</p>
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<p>Comparison of the temperature distribution at various <span class="html-italic">α</span> values at the rib height <span class="html-italic">r</span> = 0.3 (The low-temperature region distribution with different rib angles was marked by the red box).</p>
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<p>Outlet mass fraction of H<sub>2</sub> at various <span class="html-italic">α</span> values.</p>
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<p>Exergy efficiency at various <span class="html-italic">α</span> values.</p>
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20 pages, 13089 KiB  
Article
Investigating Enhanced Convection Heat Transfer in 3D Micro-Ribbed Tubes Using Inverse Problem Techniques
by Zhihui Wang, Xuguang Yang, Xiaohua Gu, Qingyong Su, Yan Liu, Xiujin He and Zhiwei Li
Energies 2024, 17(20), 5102; https://doi.org/10.3390/en17205102 - 14 Oct 2024
Viewed by 667
Abstract
The improved heat dissipation observed in 3D micro-ribbed tubes is primarily influenced by the intricate interplay of multiple structural parameters. Nevertheless, research into the coupling mechanisms of these multi-structural parameters remains constrained by the absence of effective methodology in numerical solutions. In the [...] Read more.
The improved heat dissipation observed in 3D micro-ribbed tubes is primarily influenced by the intricate interplay of multiple structural parameters. Nevertheless, research into the coupling mechanisms of these multi-structural parameters remains constrained by the absence of effective methodology in numerical solutions. In the present work, a new 3D micro-rib structure based on discrete adjoint method is established. Firstly, the research examines the interplay of different parameters (such as arrangement, relative roughness height, angle of attack, and circumferential rows) on the thermo-hydraulic performance. It is noted that the heat transfer efficiency is notably impacted by the relative roughness height. And the arrangement methodology dictates the optimal positioning for heat transfer efficiency. An increase in the number of circumferential rows enhances fluid mixing, while the angle of attack plays a crucial role in the formation of longitudinal vortices. Secondly, the coupling optimization technique is employed to obtain the optimal structure featuring non-uniform relative roughness height by the developed numerical solution. Overall, in comparison to the smooth tube, the optimized ribbed tube exhibits a remarkable 64.9% enhancement in performance evaluation criteria. Finally, a notable enhancement of 10.65–22.78% is observed when comparing with the prevailing micro-rib structures. Full article
(This article belongs to the Section J: Thermal Management)
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<p>Schematic diagram of the numerical calculation model: (<b>a</b>) calculation model; (<b>b</b>) Common–Flow–Down (D-type) arrangement; (<b>c</b>) Common–Flow–Up (U-type) arrangement.</p>
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<p>Grid independence verification: (<b>a</b>) local grid diagram; (<b>b</b>) the variation of <span class="html-italic">Nu</span> and <span class="html-italic">f</span> with the number of grids.</p>
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<p>The results of the numerical solution and the empirical formula are compared in the smooth heat exchange tube.</p>
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<p>The flow chart of the optimization process.</p>
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<p>Thermo-hydraulic characteristics for varying structural parameters: (<b>a1</b>) <span class="html-italic">Nu</span>/<span class="html-italic">Nu</span><sub>0</sub> vs. <span class="html-italic">e</span>/<span class="html-italic">D</span> at <span class="html-italic">N</span> = 4, <span class="html-italic">β</span> = 80°, (<b>a2</b>) <span class="html-italic">Nu</span>/<span class="html-italic">Nu</span><sub>0</sub> vs. <span class="html-italic">β</span> at U-type and <span class="html-italic">e</span>/<span class="html-italic">D</span> × 10 = 0.294; (<b>b1</b>) <span class="html-italic">f</span>/<span class="html-italic">f</span><sub>0</sub> vs. <span class="html-italic">e</span>/<span class="html-italic">D</span> at <span class="html-italic">N</span> = 4, <span class="html-italic">β</span> = 80°, (<b>b2</b>) <span class="html-italic">f</span>/<span class="html-italic">f</span><sub>0</sub> vs. <span class="html-italic">β</span> at U-type and <span class="html-italic">e</span>/<span class="html-italic">D</span> × 10 = 0.294; (<b>c1</b>) <span class="html-italic">PEC</span> vs. <span class="html-italic">e</span>/<span class="html-italic">D</span> at <span class="html-italic">N</span> = 4, <span class="html-italic">β</span> = 80°, (<b>c2</b>) <span class="html-italic">PEC</span> vs. <span class="html-italic">β</span> at U-type and <span class="html-italic">e</span>/<span class="html-italic">D</span> × 10 = 0.294.</p>
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<p>Thermo-hydraulic characteristics for varying structural parameters: (<b>a1</b>) <span class="html-italic">Nu</span>/<span class="html-italic">Nu</span><sub>0</sub> vs. <span class="html-italic">e</span>/<span class="html-italic">D</span> at <span class="html-italic">N</span> = 4, <span class="html-italic">β</span> = 80°, (<b>a2</b>) <span class="html-italic">Nu</span>/<span class="html-italic">Nu</span><sub>0</sub> vs. <span class="html-italic">β</span> at U-type and <span class="html-italic">e</span>/<span class="html-italic">D</span> × 10 = 0.294; (<b>b1</b>) <span class="html-italic">f</span>/<span class="html-italic">f</span><sub>0</sub> vs. <span class="html-italic">e</span>/<span class="html-italic">D</span> at <span class="html-italic">N</span> = 4, <span class="html-italic">β</span> = 80°, (<b>b2</b>) <span class="html-italic">f</span>/<span class="html-italic">f</span><sub>0</sub> vs. <span class="html-italic">β</span> at U-type and <span class="html-italic">e</span>/<span class="html-italic">D</span> × 10 = 0.294; (<b>c1</b>) <span class="html-italic">PEC</span> vs. <span class="html-italic">e</span>/<span class="html-italic">D</span> at <span class="html-italic">N</span> = 4, <span class="html-italic">β</span> = 80°, (<b>c2</b>) <span class="html-italic">PEC</span> vs. <span class="html-italic">β</span> at U-type and <span class="html-italic">e</span>/<span class="html-italic">D</span> × 10 = 0.294.</p>
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<p>Distribution of surface Nusselt number (<span class="html-italic">e</span>/<span class="html-italic">D</span> = 0.0294, <span class="html-italic">N</span> = 4, <span class="html-italic">β</span> = 80°): (<b>a</b>) D-type arrangement; (<b>b</b>) U-type arrangement.</p>
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<p>Velocity field of <span class="html-italic">x</span> = 0 mm profile at different <span class="html-italic">e</span>/<span class="html-italic">D</span>: (<b>a</b>) <span class="html-italic">e</span>/<span class="html-italic">D =</span> 0.0059; (<b>b</b>) <span class="html-italic">e</span>/<span class="html-italic">D =</span> 0.0294; (<b>c</b>) <span class="html-italic">e</span>/<span class="html-italic">D =</span> 0.0588.</p>
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<p><span class="html-italic">TKE</span> distributions of the smooth and different <span class="html-italic">N</span>-value tubes at <span class="html-italic">z</span> = 105 mm profile: (<b>a</b>) Smooth tube and <span class="html-italic">N</span> = 2–3; (<b>b</b>) <span class="html-italic">N</span> = 4–6.</p>
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<p>Tangential velocity vectors at the cross-section <span class="html-italic">z</span> = 200 mm with various <span class="html-italic">β</span>: (<b>a</b>) <span class="html-italic">β</span> = 40°; (<b>b</b>) <span class="html-italic">β</span> = 90°; (<b>c</b>) <span class="html-italic">β</span> = 160°.</p>
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<p>Coupling optimization process of various <span class="html-italic">e</span>/<span class="html-italic">D</span><sub>i</sub> (i = 1–19).</p>
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<p>Variations of <span class="html-italic">ETD</span> vs. <span class="html-italic">Re</span>.</p>
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<p>Comparisons of <span class="html-italic">PEC</span> in optimized tubes with the values in previous literatures [<a href="#B17-energies-17-05102" class="html-bibr">17</a>,<a href="#B18-energies-17-05102" class="html-bibr">18</a>,<a href="#B20-energies-17-05102" class="html-bibr">20</a>,<a href="#B37-energies-17-05102" class="html-bibr">37</a>,<a href="#B38-energies-17-05102" class="html-bibr">38</a>,<a href="#B39-energies-17-05102" class="html-bibr">39</a>].</p>
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9 pages, 3115 KiB  
Proceeding Paper
The Influence of Location of Coanda Surface Ribs on Fluidic Oscillator Performance
by Liaqat Hussain and Muhammad Mahabat Khan
Eng. Proc. 2024, 75(1), 3; https://doi.org/10.3390/engproc2024075003 - 19 Sep 2024
Viewed by 282
Abstract
Double feedback fluidic oscillators, which create oscillating fluid jets, are commonly used in flow control and thermal applications. The geometry of the Coanda surface affects the oscillation frequency, jet deflection angle, and pressure drop in the mixing chamber. This study numerically investigates the [...] Read more.
Double feedback fluidic oscillators, which create oscillating fluid jets, are commonly used in flow control and thermal applications. The geometry of the Coanda surface affects the oscillation frequency, jet deflection angle, and pressure drop in the mixing chamber. This study numerically investigates the impact of rib locations on the Coanda surface on jet characteristics. Air, with an inlet velocity of 55.8 m/s, is used as the working fluid. Three cases—full ribs, upper ribs, and lower ribs—are compared to a smooth Coanda surface. The full ribs case achieves an increased oscillation frequency of 820 Hz, compared to 355 Hz for the smooth case. However, the jet deflection angles decrease when ribs are present. The upper ribs case achieves a larger 41.5° deflection angle, while the full ribs case achieves a relatively lower 33.8° angle. Interestingly, adding ribs to the Coanda surface reduces the pressure drop in the oscillator. Oscillators with upper ribs achieve a 76.1% increase in FDPR compared to smooth cases, making them the best solution for enhancing the combined effect of jet oscillation frequency and deflection angle. Full article
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Figure 1

Figure 1
<p>All cases used in the present study.</p>
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<p>Full domain and oscillator (zoomed) mesh used in the present study.</p>
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<p>FFT analysis of velocity measurements at sampling point (6 mm and 0 mm) for various computational meshes.</p>
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<p>(<b>a</b>) Oscillation frequency and (<b>b</b>) velocity contours for different locations of ribs.</p>
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<p>Jet deflection angle for different locations of ribs.</p>
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<p>Pressure drop across fluidic oscillator for different locations of ribs.</p>
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<p>Frequency jet deflection–pressure ratio (FDPR) for different locations of ribs.</p>
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24 pages, 17443 KiB  
Article
Numerical Investigation on the Thermal Performance of a Battery Pack by Adding Ribs in Cooling Channels
by Jiadian Wang, Dongyang Lv, Haonan Sha, Chenguang Lai, Junxiong Zeng, Tieyu Gao, Hao Yang, Hang Wu and Yanjun Jiang
Energies 2024, 17(17), 4451; https://doi.org/10.3390/en17174451 - 5 Sep 2024
Cited by 1 | Viewed by 809
Abstract
The thermal performance of a lithium-ion battery pack for an electric vehicle by adding straight rib turbulators in battery cooling plate channels has been numerically investigated in this paper and the numerical model of the battery pack has been validated by experimental data, [...] Read more.
The thermal performance of a lithium-ion battery pack for an electric vehicle by adding straight rib turbulators in battery cooling plate channels has been numerically investigated in this paper and the numerical model of the battery pack has been validated by experimental data, which exhibits a satisfactory prediction accuracy. The effects of rib shapes, rib angles, rib spacings, and irregular gradient rib arrangement configurations on the flow and heat transfer behaviors of battery pack cooling plates have been thoroughly explored and analyzed in this paper. In addition, the thermal performance of the ribbed battery cooling plates was examined at actual high-speed climbing and low-temperature heating operating conditions. The results indicate that compared to the original smooth cooling plate, the square-ribbed battery cooling plate with a 60° angle and 5 mm spacing reduced the maximum battery temperature by 0.3 °C, but increased the cross-sectional temperature difference by 0.357 °C. To address this issue, a gradient rib arrangement was proposed, which slightly reduced the maximum battery temperature and lowered the cross-sectional temperature difference by 0.445 °C, significantly improving temperature uniformity. The thermal performance of the battery thermal management system with this gradient rib configuration meets the requirements for typical electric vehicle operating conditions, such as high-speed climbing and low-temperature heating conditions. Full article
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Figure 1
<p>Geometric model of battery module.</p>
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<p>Schematic diagram of (<b>a</b>) straight rib arrangement inside cooling channel, (<b>b</b>) rib shapes, (<b>c</b>) rib angles.</p>
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<p>Battery characteristics’ curve: (<b>a</b>) open-circuit voltage variation with SOC, (<b>b</b>) internal resistance variation with SOC at different ambient temperatures.</p>
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<p>The battery pack: (<b>a</b>) overall mesh, (<b>b</b>) local mesh.</p>
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<p>Grid independence test.</p>
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<p>Comparison of numeral results with experimental data [<a href="#B39-energies-17-04451" class="html-bibr">39</a>].</p>
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<p>Influence of different rib shapes on heat transfer performance: (<b>a</b>) Nusselt number, (<b>b</b>) friction factor, (<b>c</b>) thermal performance factor.</p>
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<p>Temperature contour plots of the mid-section of the battery under different straight rib cross-sectional shapes: (<b>a</b>) smooth channel, (<b>b</b>) triangular, (<b>c</b>) semicircular, (<b>d</b>) rectangular.</p>
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<p>Temperature contour plots of the battery module under different straight rib cross-sectional shapes: (<b>a</b>) smooth channel, (<b>b</b>) triangular, (<b>c</b>) semicircular, (<b>d</b>) rectangular.</p>
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<p>Cross-sectional velocity distribution contour plots for different rib shapes: (<b>a</b>) smooth channel, (<b>b</b>) triangular, (<b>c</b>) semicircular, (<b>d</b>) rectangular.</p>
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<p>Influence of different rib angles on heat transfer performance: (<b>a</b>) Nusselt number, (<b>b</b>) friction factor, and (<b>c</b>) thermal performance factor.</p>
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<p>Temperature contour plots of the battery cross-section at different rib angles: (<b>a</b>) smooth channel, (<b>b</b>) θ = 30°, (<b>c</b>) θ = 45°, (<b>d</b>) θ = 60°, (<b>e</b>) θ = 75°, (<b>f</b>) θ = 90°.</p>
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<p>Temperature contour plots of the battery module at different rib angles: (<b>a</b>) smooth channel, (<b>b</b>) θ = 30°, (<b>c</b>) θ = 45°, (<b>d</b>) θ = 60°, (<b>e</b>) θ = 75°, (<b>f</b>) θ = 90°.</p>
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<p>Cross-sectional velocity distribution contour plots: (<b>a</b>) smooth channel, (<b>b</b>) θ = 30°, (<b>c</b>) θ = 45°, (<b>d</b>) θ = 60°, (<b>e</b>) θ = 75°, (<b>f</b>) θ = 90°.</p>
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<p>Influence of different rib spacings on heat transfer performance: (<b>a</b>) Nusselt number, (<b>b</b>) friction factor, and (<b>c</b>) thermal performance factor.</p>
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<p>Temperature contour plots of the battery cross-section for different rib spacings: (<b>a</b>) smooth channel, (<b>b</b>) D = 3 mm, (<b>c</b>) D = 5 mm, (<b>d</b>) D = 10 mm.</p>
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<p>Temperature contour plots of the battery module for different rib spacings: (<b>a</b>) smooth channel, (<b>b</b>) D = 3 mm, (<b>c</b>) D = 5 mm, (<b>d</b>) D = 10 mm.</p>
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<p>Cross-sectional velocity contour plots: (<b>a</b>) smooth channel, (<b>b</b>) D = 3 mm, (<b>c</b>) D = 5 mm, (<b>d</b>) D = 10 mm.</p>
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<p>Schematic diagram of gradient rib arrangement.</p>
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<p>Simulation results for different configurations: (<b>a</b>) maximum temperature, (<b>b</b>) temperature difference, (<b>c</b>) pressure drop.</p>
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<p>Battery module temperature contour plots: (<b>a</b>) structure a, (<b>b</b>) structure b, (<b>c</b>) structure c.</p>
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<p>Cross-sectional temperature contour plots of the battery cell: (<b>a</b>) structure a, (<b>b</b>) structure b, (<b>c</b>) structure c.</p>
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<p>Simulation comparison results: (<b>a</b>) maximum temperature of battery module, (<b>b</b>) cross-sectional temperature difference within battery cell.</p>
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<p>Temperature contour plots of the battery module: (<b>a</b>) smooth channel, (<b>b</b>) gradient ribbed channel.</p>
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<p>Cross-sectional temperature contour plots of the battery cell: (<b>a</b>) smooth channel, (<b>b</b>) gradient ribbed channel.</p>
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<p>Temperature difference variation curves over time for the gradient ribbed channel and smooth channel.</p>
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<p>Temperature contour plots of the battery module: (<b>a</b>) smooth channel, (<b>b</b>) improved structure.</p>
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<p>Temperature contour plots of the battery cell cross-section: (<b>a</b>) smooth channel, (<b>b</b>) gradient ribbed channel.</p>
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<p>The variation curves of battery temperature difference over time at different temperatures.</p>
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25 pages, 5656 KiB  
Article
Dynamic Characteristics of Composite Sandwich Panel with Triangular Chiral (Tri-Chi) Honeycomb under Random Vibration
by Hui Yuan, Yifeng Zhong, Yuxin Tang and Rong Liu
Materials 2024, 17(16), 3973; https://doi.org/10.3390/ma17163973 - 9 Aug 2024
Viewed by 1039
Abstract
A full triangular chiral (Tri-Chi) honeycomb, combining a honeycomb structure with triangular chiral configuration, notably impacts the Poisson’s ratio (PR) and stiffness. To assess the random vibration properties of a composite sandwich panel with a Tri-Chi honeycomb core (CSP-TCH), a two-dimensional equivalent Reissner–Mindlin [...] Read more.
A full triangular chiral (Tri-Chi) honeycomb, combining a honeycomb structure with triangular chiral configuration, notably impacts the Poisson’s ratio (PR) and stiffness. To assess the random vibration properties of a composite sandwich panel with a Tri-Chi honeycomb core (CSP-TCH), a two-dimensional equivalent Reissner–Mindlin model (2D-ERM) was created using the variational asymptotic method. The precision of the 2D-ERM in free and random vibration analysis was confirmed through numerical simulations employing 3D finite element analysis, encompassing PSD curves and RMS responses. Furthermore, the effects of selecting the model class were quantified through dynamic numerical examples. Modal analysis revealed that the relative error of the first eight natural frequencies predicted by the 2D-ERM consistently remained below 7%, with the modal cloud demonstrating high reliability. The PSD curves and their RMS values closely aligned with 3D finite element results under various boundary conditions, with a maximum error below 5%. Key factors influencing the vibration characteristics included the ligament–rib angle of the core layer and layup modes of the composite facesheets, while the rib-to-ligament thickness ratio and the aspect ratio exert minimal influence. The impact of the ligament–rib angle on the vibration properties primarily stems from the significant shift in the core layer’s Poisson’s ratio, transitioning from negative to positive. These findings offer a rapid and precise approach for optimizing the vibration design of CSP-TCH. Full article
(This article belongs to the Special Issue Lightweight and High-Strength Sandwich Panel)
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Figure 1
<p>Several chiral structures in nature.</p>
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<p>Evolutionary progression of triangular chiral (Tri-Chi) honeycomb structures.</p>
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<p>Schematic diagram of equivalent analysis of composite sandwich panels with Tri-Chi honeycomb core (CSP-TCH).</p>
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<p>Dimensions of (<b>a</b>) core cell of Tri-Chi and (<b>b</b>) triangular chiral unit for strain energy integration.</p>
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<p>Boundary conditions for dynamic analysis of CSP-TCH. (<b>a</b>) Case 1: CCCC. (<b>b</b>) Case 2: SSCC. (<b>c</b>) Case 3: FFCC. (<b>d</b>) Case 4: FFCF.</p>
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<p>Power spectral density curve of random excitation.</p>
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<p>Comparison of displacement PSD curves predicted by 2D-ERM and 3D-FEA under (<b>a</b>) case 1: CCCC, (<b>b</b>) case 2: SSCC, (<b>c</b>) case 3: FFCC, and (<b>d</b>) case 4: FFCF.</p>
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<p>Comparison of displacement PSD curves predicted by 2D-ERM and 3D-FEA under (<b>a</b>) case 1: CCCC, (<b>b</b>) case 2: SSCC, (<b>c</b>) case 3: FFCC, and (<b>d</b>) case 4: FFCF.</p>
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<p>Comparison of acceleration PSD curves predicted by 2D-ERM and 3D-FEA under (<b>a</b>) case 1: CCCC, (<b>b</b>) case 2: SSCC, (<b>c</b>) case 3: FFCC, and (<b>d</b>) case 4: FFCF.</p>
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<p>Comparison of displacement RMS curves at the receiver point predicted by 2D-ERM and 3D-FEA under (<b>a</b>) case 1: CCCC, (<b>b</b>) case 2: SSCC, (<b>c</b>) case 3: FFCC, and (<b>d</b>) case 4: FFCF.</p>
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<p>Comparison of velocity RMS curves at the receiver point predicted by 2D-ERM and 3D-FEA under (<b>a</b>) case 1: CCCC, (<b>b</b>) case 2: SSCC, (<b>c</b>) case 3: FFCC, and (<b>d</b>) case 4: FFCF.</p>
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<p>Comparison of acceleration RMS curves at the receiver point predicted by 2D-ERM and 3D-FEA under (<b>a</b>) case 1: CCCC, (<b>b</b>) case 2: SSCC, (<b>c</b>) case 3: FFCC, and (<b>d</b>) case 4: FFCF.</p>
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<p>Influence of ligament–rib angle on the Poisson’s ratio (PR) and displacement PSD of CSP-TCH. (<b>a</b>) Poisson’s ratio. (<b>b</b>) Displacement PSD curve.</p>
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<p>Influence of thickness ratio on the Poisson’s ratio (PR) and displacement PSD of CSP-TCH. (<b>a</b>) Poisson’s ratio. (<b>b</b>) Displacement PSD curve.</p>
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<p>Influence of width–thickness ratio on the Poisson’s ratio (PR) and displacement PSD of CSP-TCH. (<b>a</b>) Poisson’s ratio. (<b>b</b>) Displacement PSD curve.</p>
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<p>Influence of layup mode on the Poisson’s ratio (PR) and displacement PSD of CSP-TCH. (<b>a</b>) Poisson’s ratio. (<b>b</b>) Displacement PSD curve.</p>
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<p>Comparison of displacement RMS curves predicted by 2D-ERM and 3D-FEA under four critical parameters. (<b>a</b>) <math display="inline"><semantics> <mi>α</mi> </semantics></math>. (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>T</mi> <mn>1</mn> </msub> <mo>/</mo> <msub> <mi>T</mi> <mn>3</mn> </msub> </mrow> </semantics></math>. (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mi>x</mi> </msub> <mo>/</mo> <msub> <mi>h</mi> <mi>c</mi> </msub> </mrow> </semantics></math>. (<b>d</b>) Layup modes.</p>
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