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์ด ๊ธฐ์ ์์ฝ์ Wenny Marthiana ์ธ ์ ์๊ฐ Jurnal Kajian Teknik Mesin (2020)์ ๋ฐํํ ๋ ผ๋ฌธ “Analisa Pengaruh Variasi Arus Listrik Pengelasan Terhadap Kekuatan Sambungan Pengelasan MIG Pada Material ST 37″์ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ, STI C&D์ ๊ธฐ์ ์ ๋ฌธ๊ฐ์ ์ํด ๋ถ์ ๋ฐ ์์ฝ๋์์ต๋๋ค.
Analisa Pengaruh Variasi Arus Listrik Pengelasan Terhadap Kekuatan Sambungan Pengelasan MIG Pada Material ST 37 (ST 37 ์์ฌ์ MIG ์ฉ์ ์ ํฉ ๊ฐ๋์ ๋ํ ์ฉ์ ์ ๋ฅ ๋ณํ์ ์ํฅ ๋ถ์)
1. Overview:
Title:ย Analisa Pengaruh Variasi Arus Listrik Pengelasan Terhadap Kekuatan Sambungan Pengelasan MIG Pada Material ST 37
Author:ย Wenny Marthiana, Yovial Mahyoedin, Duskiardi, Afri Rahim
Year of publication:ย 2020
Journal/academic society of publication:ย Jurnal Kajian Teknik Mesin Vol.5 No.2
[2] Muku and Krishna Made I Dewa, Kekuatan Sambungan Las Aluminium Seri 1100 dengan Variasi Kuat Arus Listrik Pada Proses Las Metal Inert Gas ( MIG ) Cakram, vol. 3, no. 1, pp. 11โ17, 2009.
[3] Pouranvari, M., 2011, “Effect of Welding Current on the Mechanical Response of Resistance Spot Welds of Unequal Thickhness Steel Sheets in Tensile-Shear Loading Condition: International Journal of Multidisciplinary Science and Engineering,” Vol. 2, No. 6.
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[6] W. D. Callister. 2014. Materials Science And Engineering, New Jersey. Wiley, Sixth Edition
[7] Raharjo, Samsudi & Rubijanto J.P. 2012. Variasi Arus Listrik Terhadap Sifat Mekanis Sambungan Las Shielding Metal Arc Welding (SMAW). Jurnal FT UMS, 1412-9612
[8] Syaripuddin, S., Susetyo, F. B., Aribowo, A. H., & Nofendri, Y. (2019). Kekuatan Tarik Multilapis Deposit Las Beberapa Produk Komersial Elektroda AWS A. 51 E6013. MECHANICAL, 10(1), 15-18.
This content is a summary and analysis based on the paper “Analisa Pengaruh Variasi Arus Listrik Pengelasan Terhadap Kekuatan Sambungan Pengelasan MIG Pada Material ST 37” by “Wenny Marthiana, et al.”.
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Figure 1 Isochronous curve for the electrical conductivity as a function changes in temperature for 5 h heat treatments for the AA4006TRC alloy, bottom surface.
Figure 1: Isochronous curve for the electrical conductivity as a function changes in temperature for 5 h heat treatments for the AA4006TRC alloy, bottom surface.
Figure 2: Electrical conductivity as a function of heat treatment time (solution annealing) at 550ยฐC, for samples of the AA4006 TRC alloy.
Figure 3: Electrical conductivity as a function of precipitation heat treatments at 250ยฐC and 300ยฐC, in samples of the AA4006 TRC alloys, in the sheet surface.
Figure 4: Transformed fraction as a function of isothermal time at temperatures of 250ยฐC and 300ยฐC for the AA4006 TRC alloy.
Figure 5: Linear regression of the JMAK equation in a linearized form as a function of the log of time of the fraction transformed isothermally for the temperatures of 250ยฐC and 300ยฐC.
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This content is a summary and analysis based on the paper “Effect of casting mode and thermal treatments on the electrical conductivity of the AA4006 aluminum alloy” by “Daniel Sierra Yoshikawa, et al.”.
Fig. 10 Detailed information for the Bayesian LS-SVM classifier in Fig. 9. a Square abcd, b square efhg
Figure ๋ชฉ๋ก:
Fig. 1 Collapse of Shuangyuan Bridge (2009/8/10) (photo courtesy of Apple Daily)
Fig. 2 The pressure distribution of water flow
Fig. 3 The equivalent force of water pressure when pile head is free: a the original pile; b, c the equivalent pile, d pile with equivalent force
Fig. 4 The equivalent force of water pressure when pile head is restrained: a the original pile; b, c the equivalent pile, d pile with equivalent force
Fig. 5 Using superposition to calculate pile demand: a the original pile; b the equivalent pile, c pile with original external force only, d pile with equivalent force only
Fig. 6 Water surface profile and the analyzed cross section
Fig. 7 Results of local scour depth using empirical formulae
Fig. 8 The flowchart of the proposed reliability analysis
Fig. 9 Two established classifiers for the pile head displacement
Fig. 10 Detailed information for the Bayesian LS-SVM classifier in Fig. 9. a Square abcd, b square efhg
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FIG. 1. Snapshots of the CuNiCoFe alloy, equilibrated in the VC-SGC ensemble at 800K (left) and 400K (right). The arrow highlights a clustering of copper atoms, indicating that phase separation occurs at lower temperatures.
FIG. 3. Histograms of the atomic volumes at 0K for the HEA
equilibrated at 400K (red) and 800K (blue). The dashed lines
indicate the ground state atomic volume of the single-element
FCC structures. Atomic volumes are obtained from Voronoi
tesselation38{41 of 20 snapshots at 0 K.
Figure List:
FIG. 1. Snapshots of the CuNiCoFe alloy, equilibrated in the VC-SGC ensemble at 800K (left) and 400K (right).
FIG. 2. Warren-Cowley parameters ฮฑ1 (a) and ฮฑ2 (b) for the CuNiCoFe alloy system at 800 K and 400 K. (c) The change of ฮฑ1Cu,Cu with temperature.
FIG. 3. Histograms of the atomic volumes at 0K for the HEA equilibrated at 400 K (red) and 800 K (blue).
FIG. 4. Analysis of the build-up of lattice defects during irradiation.
FIG. 5. Evolution of the SRO during irradiation.
FIG. 6. Final order parameters for the first (a) and second neighbor shell (b) after irradiation with a dose of 0.57 dpa.
FIG. 7. VC-SGC simulations of the HEA sample after irradiation.
FIG. 4. Analysis of the build-up of lattice defects during irradiation. (a) DXA analysis of the initially segregated HEA at different irradiation doses. (b) The same for a Ni sample. Empty space represents the perfect FCC lattice; the structures do not collapse during irradiation. Green lines indicate h112i partial dislocations, turquoise lines indicate a Frank loop, purple lines belong to stacking fault tetrahedra, and red surfaces enclose defects that cannot be recognized by DXA. Videos of these simulations can be found in the supplementary material (CuNiCoFe-ordered-DXA-during-irradiation.avi and Ni-DXA-during-irradiation.avi). (c) A closer look at those red regions reveals that they represent vacancies and vacancy clusters. In (d), a plot of the concentration of defective atoms as identi ed by CNA is shown as a function of the irradiation dose. In agreement with the DXA results, we can see that the HEA quickly reaches a high defect concentration that saturates around 4 %. These defects consist mostly of vacancies and small dislocation networks. Pure Ni builds up the defect concentration more slowly. At rst|similar to the HEA|vacancies and small dislocation networks appear, then these start disappearing in favor of stacking-fault tetrahedra and a Frank loop.
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This content is a summary and analysis based on the paper “Magnetostatic XFEM analysis of internal defect in uniform flux using Joukowski mapping” by “Shogo NAKASUMI, Takayuki SUZUKI”.
Source: NII-Electronic Library Service, The Japan Society of Mechanical Engineers
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์ด ๊ธฐ์ ์์ฝ์ Jan S. Wrรณbel ์ธ ์ ์๊ฐ 2020๋ ์ ๋ฐํํ ๋ ผ๋ฌธ “Elastic dipole tensors and relaxation volumes of point defects in concentrated random magnetic Fe-Cr alloys”๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ, STI C&D๊ฐ ๊ธฐ์ ์ ๋ฌธ๊ฐ๋ฅผ ์ํด ๋ถ์ ๋ฐ ์์ฝํ์์ต๋๋ค.
FIG. 1: Chemical potentials of Fe and Cr derived from fixed-volume DFT simulations. Dashed blue and red lines show the interpolated values of ฮผFe and ฮผCr as functions of Cr content. Similar trends are found in calculations involving full cell relaxation.
FIG. 2: Schematic representation of structures: (a) a Cr atom in bcc Fe, (b) a Fe atom in bcc Cr, (c) Fe-Fe, (d) Fe-Cr and (e) Cr-Cr dumbbells in bcc Fe. Fe and Cr atoms are shown as gray and blue spheres, respectively. (f) Schematic representation of atoms in the neighbourhood of a defect (white sphere). Atoms in the rst and second nearest neighbour shells are shown as red and green spheres, respectively.
*Elastic dipole tensors and relaxation volumes of point defects in concentrated random magnetic Fe-Cr alloys* (๋์ถ๋ ๋ฌด์์ ์์ฑ Fe-Cr ํฉ๊ธ ๋ด ์ ๊ฒฐํจ์ ํ์ฑ ์๊ทน์ ํ ์ ๋ฐ ์ด์ ๋ถํผ)
1. ๊ฐ์:
์ ๋ชฉ:ย Elastic dipole tensors and relaxation volumes of point defects in concentrated random magnetic Fe-Cr alloys
์ ์:ย Jan S. Wrรณbel, Marcin R. Zemลa, Duc Nguyen-Manh, Pรคr Olsson, Luca Messina, Christophe Domain, Tomasz Wejrzanowski, and Sergei L. Dudarev
FIG. 3: Schematic representation of the process of
formation of a mixed Fe-Cr dumbbell (a) by adding a
Cr atom to a Fe site and (b) by adding a Fe atom to a
Cr site. Schematic representation of formation of a
vacancy (c) on a Fe site and (d) on a Cr site. Fe and Cr
atoms are shown as gray and blue spheres, respectively.
Figure ๋ชฉ๋ก:
FIG. 1: Chemical potentials of Fe and Cr derived from fixed-volume DFT simulations.
FIG. 2: Schematic representation of structures.
FIG. 3: Schematic representation of the process of formation of a mixed Fe-Cr dumbbell.
FIG. 4: Formation energy of vacancies and SIA dumbbells in random Fe-Cr alloys.
FIG. 5: Average lattice parameter of fully relaxed Fe-Cr structures and average elastic moduli.
FIG. 6: Bulk modulus, shear modulus, Youngโs modulus and Poissonโs ratio calculated using the Voigt-Reuss-Hill method.
FIG. 7: Anisotropy of elastic properties of random Fe-Cr structures.
FIG. 8: The relaxation volumes of dumbbells in bcc Fe matrix as a function of the change in the magnitude of the total magnetic moment.
FIG. 9: Diagonal and off-diagonal elements of elastic dipole tensor for vacancies on Fe and Cr sites in random Fe-Cr alloy structures.
FIG. 10: Elements of elastic dipole tensor computed for Fe-Fe, Fe-Cr and Cr-Cr dumbbells in random Fe-Cr alloys.
FIG. 11: Invariants of elastic dipole tensors computed for vacancies and dumbbells in random Fe-Cr alloys.
FIG. 12: Invariants of relaxation volume tensor computed for vacancies and dumbbells in random Fe-Cr alloys.
FIG. 13: Relaxation volumes of vacancies and dumbbells in random Fe-Cr alloys.
FIG. 14: Relaxation volumes and formation energies of vacancies and dumbbells in random Fe-Cr alloys for the alloy with 5% at. Cr.
FIG. 15: Schematic representation of Cr-Cr dumbbell orientations.
FIG. 16: Comparison of relaxation volumes and formation energies of SIA or Fe-Fe dumbbells evaluated using the stress and cell relaxation methods.
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์ด ์ฝํ ์ธ ๋ “Jan S. Wrรณbel, et al.”์ ๋ ผ๋ฌธ “Elastic dipole tensors and relaxation volumes of point defects in concentrated random magnetic Fe-Cr alloys”๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ ์์ฝ ๋ฐ ๋ถ์ ์๋ฃ์ ๋๋ค.
์ถ์ฒ: https://arxiv.org/abs/2007.15424
๋ณธ ์๋ฃ๋ ์ ๋ณด ์ ๊ณต ๋ชฉ์ ์ผ๋ก๋ง ์ฌ์ฉ๋ฉ๋๋ค. ๋ฌด๋จ ์์ ์ ์ฌ์ฉ์ ๊ธ์งํฉ๋๋ค. Copyright ยฉ 2025 STI C&D. All rights reserved.
Figure 1: (a) Relative magnetizations of the Mn sublattices as a function of temperature assuming exchange interactions derived from the paramagnetic (DLM) state of the ideal tetragonal CuMnAs. (b) The magnetic susceptibility as a function of the temperature for such CuMnAs alloy. (c) The temperature dependence of the heat capacity for this system. In the inset we show the Binder cumulants for N = 16, 20, and 24 as a function of the temperature. The Nยดeel temperature corresponds to a common intersection of all three curves (495 K).
Paper Details
Tetragonal CuMnAs alloy: role of defects
1. Overview:
Title:ย Tetragonal CuMnAs alloy: role of defects
Author:ย F. Mรกca, J. Kudrnovskรฝ, P. Balรกลพ, V. Drchal, K. Carva, I. Turek
Year of publication:ย 2018
Journal/academic society of publication:ย arXiv:1809.06239v1 [cond-mat.mtrl-sci] (Preprint submitted to Elsevier)
Keywords:ย antiferromagnetics, defects, transport, ab initio calculations, Monte Carlo simulations
2. Abstract:
The antiferromagnetic (AFM) CuMnAs alloy with tetragonal structure is a promising material for the AFM spintronics. The resistivity measurements indicate the presence of defects about whose types and concentrations is more speculated as known. We confirmed vacancies on Mn or Cu sublattices and MnCu and CuMn antisites as most probable defects in CuMnAs by our new ab initio total energy calculations. We have estimated resistivities of possible defect types as well as resistivities of samples for which the X-ray structural analysis is available. In the latter case we have found that samples with Cu- and Mn-vacancies with low formation energies have also resistivities which agree well with the experiment. Finally, we have also calculated exchange interactions and estimated the Nรฉel temperatures by using the Monte Carlo approach. A good agreement with experiment was obtained.
Figure 1: (a) Relative magnetizations of the Mn sublattices as a function of temperature assuming exchange interactions derived from the paramagnetic (DLM) state of the ideal tetragonal CuMnAs. (b) The magnetic susceptibility as a function of the temperature for such CuMnAs alloy. (c) The temperature dependence of the heat capacity for this system. In the inset we show the Binder cumulants for N = 16, 20, and 24 as a function of the temperature. The Nรฉel temperature corresponds to a common intersection of all three curves (495 K).
Figure 2: The temperature dependence of the heat capacity derived from the paramagnetic (DLM) state of the disordered tetragonal CuMnAs alloy: (a) with Mncu-antisites (5%) and (b) with vacancies on Cu and Mn (model IIa see text). In the insets are show corresponding Binder cumulants for N = 16, 20, and 24 as a function of the temperature. The Nรฉel temperature of 465 K and 446 K has been found.
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์ด ๊ธฐ์ ์์ฝ์ Karthikeyan Hariharan๊ณผ K Sivaprasad๊ฐ ๋ฐํํ “Sustainable low-cost method for production of High entropy alloys from alloy scraps” ๋ ผ๋ฌธ์ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ, STI C&D์ ๊ธฐ์ ์ ๋ฌธ๊ฐ์ ์ํด ๋ถ์ ๋ฐ ์์ฝ๋์์ต๋๋ค.
Figure 1 XRD pattern showing peaks corresponding to different phases present in the microstructure of the as-cast CrCuFeMnNi HEA fabricated using alloy mixing method.
Figure 4 (a) Frequency distribution plot for the yield strength for alloys with varying impurity contents, (b) plot showing the variation of yield strength as a function of Si content
Figure 1 XRD pattern showing peaks corresponding to different phases present in the microstructure of the as-cast CrCuFeMnNi HEA fabricated using alloy mixing method.
Figure 2 SEM secondary electron image showing the microstructure of the as-cast CrCuFeMnNi HEA fabricated through alloy mixing; the green arrow shows the ฮฒ phase with flower-pot morphology, and the red arrow shows the ฮฑ’ phase on the phase boundary.
Figure 3 EDS maps showing different phases present and the distribution of different elements in the microstructure for the CrCuFeMnNi alloy produced using alloy mixing
Figure 4 (a) Frequency distribution plot for the yield strength for alloys with varying impurity contents, (b) plot showing the variation of yield strength as a function of Si content
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Source: The provided technical document.
This material is for informational purposes only. Unauthorized commercial use is prohibited. Copyright ยฉ 2025 STI C&D. All rights reserved.
Fig. 1 Collapse of Shuangyuan Bridge (2009/8/10) (photo courtesy of Apple Daily)
Fig. 2 The pressure distribution of water flow
Fig. 3 The equivalent force of water pressure when pile head is free: a the original pile; b, c the equivalent pile, d pile with equivalent force
Fig. 4 The equivalent force of water pressure when pile head is restrained: a the original pile; b, c the equivalent pile, d pile with equivalent force
Fig. 5 Using superposition to calculate pile demand: a the original pile; b the equivalent pile, c pile with original external force only, d pile with equivalent force only
Fig. 6 Water surface profile and the analyzed cross section
Fig. 7 Results of local scour depth using empirical formulae
Fig. 8 The flowchart of the proposed reliability analysis
Fig. 9 Two established classifiers for the pile head displacement
Fig. 10 Detailed information for the Bayesian LS-SVM classifier in Fig. 9. a Square abcd, b square efhg
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Fig.1. The experimental ERDA and simulated spectra of H and D recoils in Pd0.90Pt0.10 alloy
implanted by 25 keV deuterium ions up to fluence of ฮฆ1=1.2ร1022 D+/m2.
Fig.7. The depth concentrations of D and H atoms after 25 keV D+ ion implantation at fluence ฮฆ1=1.2ร1022 D+/m2 in pure Pd (a) and Pd0.9Rh0.1 (b) samples.
๊ทธ๋ฆผ ๋ชฉ๋ก:
Fig.1. The experimental ERDA and simulated spectra of H and D recoils in Pdโ.โโPtโ.โโ alloy implanted by 25 keV deuterium ions up to fluence of ฮฆโ=1.2ร10ยฒยฒ Dโบ/mยฒ.
Fig.2. The depth profiles of D and H atoms in Zr samples after 25 keV Dโบ implantation at two fluences: ฮฆโ=1.5ร10ยฒยฒ Dโบ/mยฒ (a) and ฮฆโโโ=2.3ร10ยฒยฒ Dโบ/mยฒ (b).
Fig.3. The depth profiles of D and H atoms in Ti samples after 25 keV Dโบ implantation at two fluences: ฮฆโ=1.8ร10ยฒยฒ ion/mยฒ (a) and ฮฆโโโ=2.3ร10ยฒยฒ ion/mยฒ (b).
Fig.4. The depth profiles of D and H atoms in AlโOโ single crystal after 25 keV Dโบ implantation at fluence ฮฆโโโ=2.3ร10ยฒยฒ Dโบ/mยฒ (b).
Fig.5. The depth profiles of D and H atoms after 25 keV Dโบ implantation at one fluence: ฮฆโ=1.5ร10ยฒยฒ Dโบ/mยฒ in Cu (a) and Stainless steel-CrโโNiโโFeโโ (b) samples.
Fig.6. The depth profiles of D and H atoms in V samples after 25 keV Dโบ implantation at two fluences: ฮฆโ=1.5ร10ยฒยฒ Dโบ/mยฒ (a) and ฮฆโโโ=2.3ร10ยฒยฒ Dโบ/mยฒ (b).
Fig.7. The depth profiles D and H atoms after 25 keV Dโบ implantation at fluence ฮฆโ=1.2ร10ยฒยฒ Dโบ/mยฒ in pure Pd (a) and Pdโ.โAgโ.โ (b) samples.
Fig.8. The depth profiles of D and H atoms after 25 keV Dโบ implantation at fluence ฮฆโ=1.2ร10ยฒยฒ Dโบ/mยฒ in the following samples Pdโ.โAgโ.โ (a, b); Pdโ.โPtโ.โ (c, d); Pdโ.โRhโ.โ (e, f); Pdโ.โRuโ.โ (g, h). The left column โ 10 days; the right column โ 3 month after the implantation.
Fig. 9. Size distribution of scatterers in ion implanted titanium and corundum.
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FIG. 1. Thermodynamic modeling (T=400โฆ C) of the net doping log(|NDโNA|/cmโ3) in Cu2โ2x(II)xO1โy(VI)y alloys as a function of x and y for 4 different II/VI combinations. ND and NA are individual concentrations of donors and acceptors, respectively. The sign indicates the type of doping (positive for p-type, negative for n-type). The band gap values extrapolated according to eq. (2) are given for the end compositions for 0 (x, y) 0.2.
FIG. 1. Thermodynamic modeling (T=400ยฐ C) of the net doping log(|ND – NA|/cmยฏยณ) in Cu2โ2x (II)xO1โy(VI)y alloys as a function of x and y for 4 different II/VI combinations.
FIG. 2. (a) Cuprite Cu2O structure with O atoms shown in red and Cu in blue; (b) structure of a (II)2Cu defect pair, where one metal impurity (II=Mg, Zn, Cd) shown in grey replaces two copper atoms Cuโ1 and Cu2; (c) defect and defect-pair formation energies of Vcu, group II cation impurities (II=Zn) and and group VI anion impurities (VI=S) as a function of the Fermi energy, assuming phase coexistence of Cu2O with ZnO and Cu2S.
FIG. 3. Thermodynamic modeling of defect and dopant concentrations in Cu2O.
FIG. 4. (a) X-ray diffraction patterns of Cu2O (black), Cu2-2xZnO (red) and Cu2O1-ySey (blue) thin films on a-SiO2, 44 patterns each. (b) Lattice constant of Cu2O (black), Cu2-2xZnO (red) and Cu2O1-ySey (blue) alloys from experiment (symbols) and computations (lines)
FIG. 5. Same as Fig. 1, but for (II) = Zn.
FIG. 6. Same as Fig. 1, but for (II) = Mg.
FIG. 7. Same as Fig. 1, but for (II) = Cd.
FIG. 8. Composition dependence of the VBM (top row) and CBM (bottom row) energies.
FIG. 9. Composition dependence of the defect formation energy โHD,q (EF) of the negatively charged Vcu defect (top row) and of the positively charged substitutional cation-site donor (bottom row).
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This content is a summary and analysis based on the paper “Optimisasi Jarak Titik Spot welding Terhadap Tensile Strength Sambungan Stainless Steel” by “Sobron Lubis, Aghastya Wiyoso, Jhon Michel, Benaya”.
Source: http://ejournal2.pnp.ac.id/index.php/jtm
This material is for informational purposes only. Unauthorized commercial use is prohibited. Copyright ยฉ 2025 STI C&D. All rights reserved.
์ด ๊ธฐ์ ์์ฝ์ Cut Suciatina Silvia, Muhammad Ikhsan, Azwanda๊ฐ ์์ฑํ์ฌ Journal of Civil Engineering Forum (2021)์ ๋ฐํํ ํ์ ๋ ผ๋ฌธ “The Effect of Bridge Piers on Local Scouring at Alue Buloh Bridge Nagan Raya Regency”๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํฉ๋๋ค. STI C&D์ ๊ธฐ์ ์ ๋ฌธ๊ฐ๋ค์ด ๋ถ์ํ๊ณ ์์ฝํ์ต๋๋ค.
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์ด ์ฝํ ์ธ ๋ “The Effect of Bridge Piers on Local Scouring at Alue Buloh Bridge Nagan Raya Regency” (์ ์: Cut Suciatina Silvia, Muhammad Ikhsan, Azwanda) ๋ ผ๋ฌธ์ ๊ธฐ๋ฐ์ผ๋ก ํ ์์ฝ ๋ฐ ๋ถ์ ์๋ฃ์ ๋๋ค.
์ถ์ฒ: https://doi.org/10.22146/jcef.57719
์ด ์๋ฃ๋ ์ ๋ณด ์ ๊ณต ๋ชฉ์ ์ผ๋ก๋ง ์ฌ์ฉ๋ฉ๋๋ค. ๋ฌด๋จ ์์ ์ ์ฌ์ฉ์ ๊ธํฉ๋๋ค. Copyright ยฉ 2025 STI C&D. All rights reserved.
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์ด ๊ธฐ์ ์์ฝ์ Luke J. Prendergast ์ธ ์ ์๊ฐ Structural Engineering International (2018)์ ๋ฐํํ ๋ ผ๋ฌธ “Structural Health Monitoring for Performance Assessment of Bridges under Flooding and Seismic Actions”์ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ, STI C&D๊ฐ ๊ธฐ์ ์ ๋ฌธ๊ฐ๋ฅผ ์ํด ๋ถ์ํ๊ณ ์์ฝํ์ต๋๋ค.
Fig. 3: Failure due to seismic action: (a) slab unseating in Japan, 1964 (ยฉ The Japanese Geotechnical Society); (b) slab unseating in the US, 1989 (Credit: U.S. Geological Survey/photo by C.E. Meyer)
Fig.6: Seismic input ground acceleration for the 1999 Athens earthquake:(a)time history; (b)spectrum of ground acceleration
Figure List:
Fig. 1: Arch-bridge damage scenarios: (a) failure under symmetrical scour; (b) failure under asymmetrical scour
Fig. 2: An example of poor seismic design: the Hyogo-Ken Nanbu earthquake in Japan, 1995
Fig. 3: Failure due to seismic action: (a) slab unseating in Japan, 1964; (b) slab unseating in the US, 1989
Fig. 4: Schematic of the non-linear numerical bridge model used in the case study (Units: m)
Fig. 5: Bridge mode shapes under zero and 10 m scour of Pier 4: (a) mode 1 of the bridge โ no scour, (b) mode 1 of the bridge โ 10 m scour, (c) mode 2 of the bridge โ no scour, (d) mode 2 of the bridge -10 m scour
Fig. 6: Seismic input ground acceleration for the 1999 Athens earthquake: (a) time history; (b) spectrum of ground acceleration
Fig. 7: Seismic response of the bridge deck (lateral) at Pier 4 under progressive scour conditions
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This content is a summary and analysis based on the paper “Optimization of Submerged Arc Welding process Parameters Using PCA-Based Taguchi Approach.” by “P. Sreeraj”.
Source: International Journal of Integrated Engineering, Vol. 8 No. 3 (2016) p. 21-32
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Fig. 3. X-axis:Variation of Vickersโs hardness number with wt % of Mo. Y-axis: Vickers Hardness Number (VPN)
Fig. 4. Variation of tensile strength(Y- axis) with wt.% of molybdenum(X axis)
Figure ๋ชฉ๋ก:
Fig. 1 Graph between voltage, welding speed and mean of s/n ratio
Fig. 2. (a)- (k) Microstructure of base metal, interzone and weldzone in different cases BS-bainitic shelves, PF- polygonal ferrite, AF- acicular ferrite)
Fig. 3. X-axis: Variation of Vickers’s hardness number with wt % of Mo. Y-axis: Vickers Hardness Number (VPN)
Fig. 4. Variation of tensile strength(Y- axis) with wt.% of molybdenum(X axis)
Fig. 5. a) SEM Points taken from weld zone(WZ) to HAZ on sample. b) EDS Molybdenum distribution in the matrix with 0.05 % Mo.
Fig. 6. a) SEM Points taken from weld zone (WZ) to HAZ on sample, b) EDS Molybdenum distribution in the matrix with 0.20% Mo.
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This content is a summary and analysis based on the paper “NUMERICAL SIMULATION OF INTERSECTING LINE WORKPIECE WELDED BY ARC ROBOT WELDING” by “H.W. WU, Y. Q. CAI, Z. H. GENG”.
Source: METALURGIJA 63 (2024) 3-4, 407-409
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This content is a summary and analysis based on the paper “Using artificial neural networks to identify and optimise the key parameters affecting geometry of a GMAW fillet weld” by “Cairns, Jonathan and McPherson, Norman and Galloway, Alexander”.
Source: http://strathprints.strath.ac.uk/53412/
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์ด ๊ธฐ์ ์์ฝ์ Ana Margarida Bento ์ธ ์ ์๊ฐ Book of Abstracts, Civil Engineering Symposium์ ๋ฐํํ ๋ ผ๋ฌธ “Photogrammetric characterization of the scour cavity time evolution around a complex bridge pier”๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํฉ๋๋ค. STI C&D์ ๊ธฐ์ ์ ๋ฌธ๊ฐ๋ค์ด ๋ถ์ํ๊ณ ์์ฝํ์ต๋๋ค.
Photogrammetric characterization of the scour cavity time evolution around a complex bridge pier (๋ณต์กํ ๊ต๊ฐ ์ฃผ๋ณ ์ธ๊ตด ๊ณต๋์ ์๊ฐ์ ๋ณํ์ ๋ํ ์ฌ์ง์ธก๋ํ์ ํน์ฑํ)
1. ๊ฐ์:
์ ๋ชฉ:ย Photogrammetric characterization of the scour cavity time evolution around a complex bridge pier
์ ์:ย Ana Margarida Bentoยน, Pedro Xavier Ramosยฒ, Rodrigo Maiaยณ, Joรฃo Pedro Pรชgoโด
๋ฐํ ์ฐ๋:
ํ์ ์ง/ํํ:ย Book of Abstracts, Civil Engineering Symposium
ํค์๋:ย complex bridge pier, local scour, scour cavity, close-range photogrammetry
Moreno, M., Maia, R., Couto L. and Cardoso. H. 2012. โEvaluation of local scour depth around complex bridge piers”. River Flow – International Conference on Fluvial Hydraulics, San Jose (Costa Rica).
Rapp, C. and Eder, K. 2012. โ3D determination of the sour evolution around a bridge pier by photogrammetric means.โ Proc. Int. Conf. River Flow 2012, 943-950, R.M. Munoz, eds.
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This content is a summary and analysis based on the paper “Pitting corrosion characteristics of gas tungsten arc welded austenitic steel” by “Abraham M. Afabor, Basil O. Onyekpe, Oghenerobo Awheme and Cyril O. Uyeri”.
Source: http://dx.doi.org/10.5599/jese.2615
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GUIDELINES FOR DATA COLLECTION AND MONITORING FOR ASSET MANAGEMENT OF NEW ZEALAND ROAD BRIDGES
1. Overview:
Title:ย GUIDELINES FOR DATA COLLECTION AND MONITORING FOR ASSET MANAGEMENT OF NEW ZEALAND ROAD BRIDGES
Author:ย Dr Piotr Omenzetter (The University of Auckland), Simon Bush (Opus International Consultants Ltd), Peter McCarten (Opus International Consultants Ltd)
Year of publication:ย 2015
Journal/academic society of publication:ย RIMS (Roading Infrastructure Management Support), IPWEA (INSTITUTE OF PUBLIC WORKS ENGINEERING AUSTRALASIA), Road Controlling AUTHORITIES FORUM (NZ) ING
Keywords:ย Asset Management, Road Bridges, Data Collection, Monitoring, Risk Assessment, Criticality, New Zealand
๋ฆฌ์คํฌ ํ๊ฐ ๊ณต์์ R = H x V x C x U๋ก ์ ์ํ๊ณ , ๊ฐ ์์(์ํ, ์ทจ์ฝ์ฑ, ๊ฒฐ๊ณผ, ๋ถํ์ค์ฑ)์ ๋ํ ์ ๋์ ์ ์ ์ฐ์ ๊ธฐ์คํ๋ฅผ ์ ๊ณตํ์ฌ ํ๊ฐ์ ์ผ๊ด์ฑ๊ณผ ๊ฐ๊ด์ฑ์ ํ๋ณดํ์ต๋๋ค.
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Phares, B. M., A. W. Glenn, et al. (2004). “Routine Highway Bridge Inspection Condition Documentation Accuracy and Reliability.โ Journal of Bridge Engineering 9(4): 403-413.
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This content is a summary and analysis based on the paper “GUIDELINES FOR DATA COLLECTION AND MONITORING FOR ASSET MANAGEMENT OF NEW ZEALAND ROAD BRIDGES” by “Dr Piotr Omenzetter, Simon Bush, Peter McCarten”.
Source: The document itself is the source, published by RIMS, IPWEA, and Road Controlling Authorities Forum (NZ) INC in March 2015.
This material is for informational purposes only. Unauthorized commercial use is prohibited. Copyright ยฉ 2025 STI C&D. All rights reserved.
In this study, the application of a machine learning model, namely the adaptive neuro-fuzzy inference system (ANFIS) is proposed to estimate the scour depth around bridge piers. In particular, various complexity architectures are sequentially developed, trained and validated using appropriate training and validation subsets obtained from the USGS database. The raw data are pre-processed to remove incomplete records and randomly split into the training and validation data sets which are both representative of the same space. The model has five parameters, namely the effective pier width (b), the approach velocity (U), the approach depth (y), the mean grain diameter (D50) and the skew to flow. Simulations are conducted with data groups (bed material type, pier type and shape) and different number and combinations of input variables, to produce reduced complexity and easily interpretable models. Analysis and comparison of the results indicate that the developed ANFIS model has high accuracy and outstanding generalization ability for prediction of scour parameters. The optimal ANFIS models are identified utilizing appropriate error metrics. The effective pier width (as opposed to skew to flow) is amongst the most relevant input parameters for the estimation. The developed models can be used as a scour prediction tool performing satisfactorily even in the presence of scarce available data, while empirical rules can be also derived for the reduced order models.
Figure 1. Generic example of an ANFIS architecture
Figure 2. Plot of observed and predicted scour depth training the model with all input parameters with the subset of single round pier data: a) performance for the training subset (77 data points) and b) performance for the validation data set (74 data points). Note the line of perfect agreement is shown with the straight line (diagonal).
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This content is a summary and analysis based on the paper “Prediction Of Scour Depth Around Bridge Piers Using Adaptive Neuro-Fuzzy Inference Systems (ANFIS)” by “Manousos Valyrakis, Hanqing Zhang”.
์ด ๊ธฐ์ ์์ฝ์ Hsiao-Wen, Wang ์ธ ์ ์๊ฐ 2014๋ Journal of Chinese Soil and Water Conservation์ ๋ฐํํ ๋ ผ๋ฌธ “NETSTARS Improvement with Pier Scouring – A Case Study of Pa-Chang River”๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ, STI C&D์ ๊ธฐ์ ์ ๋ฌธ๊ฐ์ ์ํด ๋ถ์ ๋ฐ ์์ฝ๋์์ต๋๋ค.
NETSTARS ๆจกๅผๅ ๅ ฅๆฉๅขฉๆฒๅทๅ่ฝไน็ ็ฉถโโไปฅๅ ซๆๆบช็บไพ (NETSTARS Improvement with Pier Scouring – A Case Study of Pa-Chang River)
1. Overview:
Title:ย NETSTARS ๆจกๅผๅ ๅ ฅๆฉๅขฉๆฒๅทๅ่ฝไน็ ็ฉถโโไปฅๅ ซๆๆบช็บไพ (NETSTARS Improvement with Pier Scouring – A Case Study of Pa-Chang River)
This study applies NETSTARS V3.0 by adding the calculation functions of eighteen pier scour formulas based on a comprehensive literature review to demonstrate local scour mechanisms. The study area is a reach of the Pachang Creek from the Housheng Bridge to the Chukou Bridge. We do not set the structures and weirs in the river to be scoured. Simulations are conducted by setting boundary conditions and importing information about nineteen bridges, and validations are separated into two steps as: general scouring and bridge local scouring. The best parameters are qualified by computing error evaluated parameter to fit the changing tendencies of the Pachang Creek. Finally, long-term riverbed evolution is simulated. The results show that there are 5 bridges with erosion trends. The results can be used as a reference for one-dimensional numerical models with pier scouring functions.
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This content is a summary and analysis based on the paper “NETSTARS Improvement with Pier Scouring – A Case Study of Pa-Chang River” by “Hsiao-Wen, Wang et al.”.
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“At STI C&D, we are committed to applying the latest industry research to help our customers achieve higher productivity and quality. If the challenges discussed in this paper align with your operational goals, contact our engineering team to explore how these principles can be implemented in your components.”
This content is a summary and analysis based on the paper “Process Simulation of Resistance Weld Bonding and Automotive Light-weight Materials” by “Zhang, Wenqi; Chergui, Azeddine; Nielsen, Chris Valentin”.
Overview: Title: Incerteza na Mediรงรฃo dos Parรขmetros Geomรฉtricos do Cordรฃo de Solda (Measurement Uncertainty of Geometric Parameters in Weld Beads) Author: Rosenda Valdรฉs Arencibia, Eduardo Manuel Dรญaz Cedrรฉ, Amado Cruz Crespo, Antonio Piratelli-Filho Year of publication: 2011 Journal/academic society of publication: Soldagem & Inspeรงรฃo, Sรฃo Paulo Keywords: Soldagem, geometria do cordรฃo de solda, incerteza de mediรงรฃo, planeza, perpendicularidade (Welding, weld bead geometry, uncertainty, flatness, perpendicularity)
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์ฐ๋ฝ์ฒ : 02-2026-0450 ์ด๋ฉ์ผ : flow3d@stikorea.co.kr Copyright Information This content is a summary and analysis based on the paper “Incerteza na Mediรงรฃo dos Parรขmetros Geomรฉtricos do Cordรฃo de Solda” by “Rosenda Valdรฉs Arencibia, et al.”. Source: http://dx.doi.org/10.1590/S0104-92242011000100009 This material is for informational purposes only. Unauthorized commercial use is prohibited. Copyright ยฉ 2025 STI C&D. All rights reserved.
์ด ๊ธฐ์ ์์ฝ์ Erion PERIKU์ Yavuz YARDIM์ด ์์ฑํ์ฌ International Students’ Conference of Civil Engineering, ISCCE 2012์ ๋ฐํํ “[Effect of Scour on Load Carry Capacity of Piles on Mat Bridge]” ๋ ผ๋ฌธ์ ๋ฐํ์ผ๋ก STI C&D์ ๊ธฐ์ ์ ๋ฌธ๊ฐ์ ์ํด ๋ถ์ ๋ฐ ์์ฝ๋์์ต๋๋ค.
Effect of Scour on Load Carry Capacity of Piles on Mat Bridge
1. Overview:
Title: Effect of Scour on Load Carry Capacity of Piles on Mat Bridge
Author: Erion PERIKU, Yavuz YARDIM
Year of publication: 2012
Journal/academic society of publication: International Students’ Conference of Civil Engineering, ISCCE 2012, 10-11 May 2012, EpokaUniversity, Tirana, Albania
Keywords: Mat Bridge, Scour, Pile Bent, Pile Load Carry Capacity.
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This content is a summary and analysis based on the paper “Effect of Scour on Load Carry Capacity of Piles on Mat Bridge” by “Erion PERIKU, Yavuz YARDIM”.
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This content is a summary and analysis based on the paper “Assessing equilibrium clear water scour around single cylindrical piers” by “Rui Lanรงa, Cristina Fael, Antรณnio Cardoso”.
Source: The time records of the scour depth are available at http://w3.ualg.pt/~rlanca/riverflow2010.htm
This material is for informational purposes only. Unauthorized commercial use is prohibited. Copyright ยฉ 2025 STI C&D. All rights reserved.
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์ด ์๊ฐ์๋ฃ๋ Water Resources Engineering Journal Spring 2022. Vol 15. Issue 52์ ๊ฐ์ ๋ Numerical simulation of geotechnical effects on local scour in inclined pier group with Flow-3D software ๋ ผ๋ฌธ์ ๋ํ ์๊ฐ์๋ฃ์ ๋๋ค.
Figure 10 โ Scour pit around pile group with different pile cap installation levels
Figure 10 โ Scour pit around pile group with different pile cap installation levels
Figure 11 – Final longitudinal scour profile for different pile cap installation levels a) Above the bed (Z/Tp = 0), b) At the bed level (Z/Tp = -1), c) Below the bed (Z/Tp = -2)
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Figure 2: Developed model in flow-3d for single pier.
Figure 9: 3D maximum sour around single pier (no initial flow)
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๋ณธ ์๊ฐ ์๋ฃ๋ International Symposium on Hydraulic Structures์์ ๋ฐํํ “Performance Assessment of FLOW-3D and XFlow in the Numerical Modelling of Fish-bone Type Fishway Hydraulics” ๋ ผ๋ฌธ์ ๊ธฐ๋ฐ์ผ๋ก ํฉ๋๋ค.
Figure 1. Three main regions in the fish-bone-type fishway.
Figure 1. Three main regions in the fish-bone-type fishway.Figure 3. Stream traces for (a) FLOW-3D and (b) XFlow at 0.075 m3
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Md Didarul Islam, Himendra Perera, Benjamin Black, Matthew Phillips,Muh-Jang Chen, Greyson Hodges, Allyce Jackman, Yuxuan Liu, Chang-Jin Kim,Mohammed Zikry, Saad Khan, Yong Zhu, Mark Pankow, and Jong Eun Ryu
Abstract
Periodic micro/nanoscale structures from nature have inspired the scientific community to adopt surface design for various applications, including superhydrophobic drag reduction. One primary concern of practical applications of such periodic microstructures remains the scalability of conventional microfabrication technologies. This study demonstrates a simple template-free scalable manufacturing technique to fabricate periodic microstructures by controlling the ribbing defects in the forward roll coating. Viscoelastic composite coating materials are designed for roll-coating using carbon nanotubes (CNT) and polydimethylsiloxane (PDMS), which helps achieve a controllable ribbing with a periodicity of 114โ700 ยตm. Depending on the process parameters, the patterned microstructures transition from the linear alignment to a random structure. The periodic microstructure enables hydrophobicity as the water contact angles of the samples ranged from 128ยฐ to 158ยฐ. When towed in a static water pool, a model boat coated with the microstructure film shows 7%โ8% faster speed than the boat with a flat PDMS film. The CNT addition shows both mechanical and electrical properties improvement. In a mechanical scratch test, the cohesive failure of the CNT-PDMS film occurs in โ90% higher force than bare PDMS. Moreover, the nonconductive bare PDMS shows sheet resistance of 747.84โ22.66 ฮฉ โกโ1 with 0.5 to 2.5 wt% CNT inclusion.
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Mohammad Nazari-Sharabian, Aliasghar Nazari-Sharabian, Moses Karakouzian, Mehrdad Karami
Abstract
Scour is defined as the erosive action of flowing water, as well as the excavating and carrying away materials from beds and banks of streams, and from the vicinity of bridge foundations, which is one of the main causes of river bridge failures. In the present study, implementing a numerical approach, and using the FLOW-3D model that works based on the finite volume method (FVM), the applicability of using sacrificial piles in different configurations in front of a bridge pier as countermeasures against scouring is investigated. In this regard, the numerical model was calibrated based on an experimental study on scouring around an unprotected circular river bridge pier. In simulations, the bridge pier and sacrificial piles were circular, and the riverbed was sandy. In all scenarios, the flow rate was constant and equal to 45 L/s. Furthermore, one to five sacrificial piles were placed in front of the pier in different locations for each scenario. Implementation of the sacrificial piles proved to be effective in substantially reducing the scour depths. The results showed that although scouring occurred in the entire area around the pier, the maximum and minimum scour depths were observed on the sides (using three sacrificial piles located upstream, at three and five times the pier diameter) and in the back (using five sacrificial piles located upstream, at four, six, and eight times the pier diameter) of the pier. Moreover, among scenarios where single piles were installed in front of the pier, installing them at a distance of five times the pier diameter was more effective in reducing scour depths. For other scenarios, in which three piles and five piles were installed, distances of six and four times the pier diameter for the three piles scenario, and four, six, and eight times the pier diameter for the five piles scenario were most effective.
Keywords
Scouring; River Bridges; Sacrificial Piles; Finite Volume Method (FVM); FLOW-3D.
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Waqed H. Hassanย |ย Zahraa Mohammad Fadhe*ย |ย Rifqa F. Thiabย |ย Karrar Mahdi Civil Engineering Department, Faculty of Engineering, University of Warith Al-Anbiyaa, Kerbala 56001, Iraq Civil Engineering Department, Faculty of Engineering, University of Kerbala, Kerbala 56001, Iraq Corresponding Author Email:ย Waqed.hammed@uowa.edu.iq
OPEN ACCESS
Abstract:
This work investigates numerically a local scour moves in irregular waves around tripods. It is constructed and proven to use the numerical model of the seabed-tripod-fluid with an RNG k turbulence model. The present numerical model then examines the flow velocity distribution and scour characteristics. After that, the suggested computational model Flow-3D is a useful tool for analyzing and forecasting the maximum scour development and the flow field in random waves around tripods. The scour values affecting the foundations of the tripod must be studied and calculated, as this phenomenon directly and negatively affects the structure of the structure and its design life. The lower diagonal braces and the main column act as blockages, increasing the flow accelerations underneath them. This increases the number of particles that are moved, which in turn creates strong scouring in the area. The numerical model has a good agreement with the experimental model, with a maximum percentage of error of 10% between the experimental and numerical models. In addition, Based on dimensional analysis parameters, an empirical equation has been devised to forecast scour depth with flow depth, median size ratio, Keulegan-Carpenter (Kc), Froud number flow, and wave velocity that the results obtained in this research at various flow velocities and flow depths demonstrated that the maximum scour depth rate depended on wave height with rising velocities and decreasing particle sizes (d50) and the scour depth attains its steady-current value for Vw < 0.75. As the Froude number rises, the maximum scour depth will be large.
Keywords:
local scour, tripod foundation, Flow-3Dโ, waves
1. Introduction
New energy sources have been used by mankind since they become industrialized. The main energy sources have traditionally been timber, coal, oil, and gas, but advances in the science of new energies, such as nuclear energy, have emerged [1, 2]. Clean and renewable energy such as offshore wind has grown significantly during the past few decades. There are numerous different types of foundations regarding offshore wind turbines (OWTs), comprising the tripod, jacket, gravity foundation, suction anchor (or bucket), and monopile [3, 4]. When the water depth is less than 30 meters, Offshore wind farms usually employ the monopile type [4]. Engineers must deal with the wind’s scouring phenomenon turbine foundations when planning and designing wind turbines for an offshore environment [5]. Waves and currents generate scour, this is the erosion of soil near a submerged foundation and at its location [6]. To predict the regional scour depth at a bridge pier, Jalal et al. [7-10] developed an original gene expression algorithm using artificial neural networks. Three monopiles, one main column, and several diagonal braces connecting the monopiles to the main column make up the tripod foundation, which has more complicated shapes than a single pile. The design of the foundation may have an impact on scour depth and scour development since the foundation’s form affects the flow field [11, 12]. Stahlmann [4] conducted several field investigations. He discovered that the main column is where the greatest scour depth occurred. Under the main column is where the maximum scour depth occurs in all experiments. The estimated findings show that higher wave heights correspond to higher flow velocities, indicating that a deeper scour depth is correlated with finer silt granularity [13] recommends as the design value for a single pile. These findings support the assertion that a tripod may cause the seabed to scour more severely than a single pile. The geography of the scour is significantly more influenced by the KC value (KeuleganโCarpenter number)
The capability of computer hardware and software has made computational fluid dynamics (CFD) quite popular to predict the behavior of fluid flow in industrial and environmental applications has increased significantly in recent years [14].
Finding an acceptable piece of land for the turbine’s construction and designing the turbine pile precisely for the local conditions are the biggest challenges. Another concern related to working in a marine environment is the effect of sea waves and currents on turbine piles and foundations. The earth surrounding the turbine’s pile is scoured by the waves, which also render the pile unstable.
In this research, the main objective is to investigate numerically a local scour around tripods in random waves. It is constructed and proven to use the tripod numerical model. The present numerical model is then used to examine the flow velocity distribution and scour characteristics.
2. Numerical Model
To simulate the scouring process around the tripod foundation, the CFD code Flow-3D was employed. By using the fractional area/volume method, it may highlight the intricate boundaries of the solution domain (FAVOR).
This model was tested and validated utilizing data derived experimentally from Schendel et al. [15] and Sumer and Fredsรธe [6]. 200 runs were performed at different values of parameters.
2.1 Momentum equations
The incompressible viscous fluid motion is described by the three RANS equations listed below [16]:
where, respectively, u, v, and w represent the x, y, and z flow velocity components; volume fraction (VF), area fraction (Ai; I=x, y, z), water density (f), viscous force (fi), and body force (Gi) are all used in the formula.
2.2 Model of turbulence
Several turbulence models would be combined to solve the momentum equations. A two-equation model of turbulence is the RNG k-model, which has a high efficiency and accuracy in computing the near-wall flow field. Therefore, the flow field surrounding tripods was captured using the RNG k-model.
2.3 Model of sediment scour
2.3.1 Induction and deposition
Eq. (4) can be used to determine the particle entrainment lift velocity [17].
ฮฑ๐ผi is the Induction parameter, ns the normal vector is parallel to the seafloor, and for the present numerical model, ns=(0,0,1), ฮธ๐cr is the essential Shields variable, g is the accelerated by gravity, di is the size of the particles, ฯi is species density in beds, and dโ The diameter of particles without dimensions; these values can be obtained in Eq. (5).
fbis the essential particle packing percentage, qb, i is the bed load transportation rate, and cb, I the percentage of sand by volume i. These variables can be found in Eq. (9), Eq. (10), fb, ฮด๐ฟi the bed load thickness.
In this paper, after the calibration of numerous trials, the selection of parameters for sediment scour is crucial. Maximum packing fraction is 0.64 with a shields number of 0.05, entrainment coefficient of 0.018, the mass density of 2650, bed load coefficient of 12, and entrainment coefficient of 0.01.
3. Model Setup
To investigate the scour characteristics near tripods in random waves, the seabed-tripod-fluid numerical model was created as shown in Figure 1. The tripod basis, a seabed, and fluid and porous medium were all components of the model. The seabed was 240 meters long, 40 meters wide, and three meters high. It had a median diameter of d50 and was composed of uniformly fine sand. The 2.5-meter main column diameter D. The base of the main column was three dimensions above the original seabed. The center of the seafloor was where the tripod was, 130 meters from the offshore and 110 meters from the onshore. To prevent wave reflection, the porous media were positioned above the seabed on the onshore side.
Figure 1. An illustration of the numerical model for the seabed-tripod-fluid
3.1 Generation of meshes
Figure 2 displays the model’s mesh for the Flow-3D software grid. The current model made use of two different mesh types: global mesh grid and nested mesh grid. A mesh grid with the following measurements was created by the global hexahedra mesh grid: 240m length, 40m width, and 32m height. Around the tripod, a finer nested mesh grid was made, with dimensions of 0 to 32m on the z-axis, 10 to 30 m on the x-axis, and 25 to 15 m on the y-axis. This improved the calculation’s precision and mesh quality.
To increase calculation efficiency, the top side, The model’s two x-z plane sides, as well as the symmetry boundaries, were all specified. For u, v, w=0, the bottom boundary wall was picked. The offshore end of the wave boundary was put upstream. For the wave border, random waves were generated using the wave spectrum from the Joint North Sea Wave Project (JONSWAP). Boundary conditions are shown in Figure 3.
Figure 3. Boundary conditions of the typical problem
The wave spectrum peak enhancement factor (=3.3 for this work) and can be used to express the unidirectional JONSWAP frequency spectrum.
3.3 Mesh sensitivity
Before doing additional research into scour traits and scour depth forecasting, mesh sensitivity analysis is essential. Three different mesh grid sizes were selected for this section: Mesh 1 has a 0.45 by 0.45 nested fine mesh and a 0.6 by 0.6 global mesh size. Mesh 2 has a 0.4 global mesh size and a 0.35 nested fine mesh size, while Mesh 3 has a 0.25 global mesh size and a nested fine mesh size of 0.15. Comparing the relative fine mesh size (such as Mesh 2 or Mesh 3) to the relatively coarse mesh size (such as Mesh 1), a larger scour depth was seen; this shows that a finer mesh size can more precisely represent the scouring and flow field action around a tripod. Significantly, a lower mesh size necessitates a time commitment and a more difficult computer configuration. Depending on the sensitivity of the mesh guideline utilized by Pang et al., when Mesh 2 is applied, the findings converge and the mesh size is independent [20]. In the next sections, scouring the area surrounding the tripod was calculated using Mesh 2 to ensure accuracy and reduce computation time. The working segment generates a total of 14, 800,324 cells.
3.4 Model validation
Comparisons between the predicted outcomes from the current model and to confirm that the current numerical model is accurate and suitably modified, experimental data from Sumer and Fredsรธe [6] and Schendel et al. [15] were used. For the experimental results of Run 05, Run 15, and Run 22 from Sumer and Fredsรธe [6], the experimental A9, A13, A17, A25, A26, and A27 results from Schendel et al. [15], and the numerical results from the current model are shown in Figure 4. The present model had d50=0.051cm, the height of the water wave(h)=10m, and wave velocity=0.854 m.s-1.
Figure 5. Comparison of the present study’s maximum scour depth with that authored by Sumer and Fredsรธe [6] and Schendel et al. [15]
According to Figure 5, the highest discrepancy between the numerical results and experimental data is about 10%, showing that overall, there is good agreement between them. The ability of the current numerical model to accurately depict the scour process and forecast the maximum scour depth (S) near foundations is demonstrated by this. Errors in the simulation were reduced by using the calibrated values of the parameter. Considering these results, a suggested simulated scouring utilizing a Flow-3D numerical model is confirmed as a superior way for precisely forecasting the maximum scour depth near a tripod foundation in random waves.
3.5 Dimensional analysis
The variables found in this study as having the greatest impacts, variables related to flow, fluid, bed sediment, flume shape, and duration all had an impact on local scouring depth (t). Hence, scour depth (S) can be seen as a function of these factors, shown as:
With the aid of dimensional analysis, the 14-dimensional parameters in Eq. (11) were reduced to 6 dimensionless variables using Buckingham’s -theorem. D, V, and were therefore set as repetition parameters and others as constants, allowing for the ignoring of their influence. Eq. (12) thus illustrates the relationship between the effect of the non-dimensional components on the depth of scour surrounding a tripod base.
(12)
\frac{S}{D}=f\left(\frac{h}{D}, \frac{d 50}{D}, \frac{V}{V W}, F r, K c\right)
where, SD๐๐ท are scoured depth ratio, VVw๐๐๐ค is flow wave velocity, d50D๐50๐ท median size ratio, $Fr representstheFroudnumber,and๐๐๐๐๐๐ ๐๐๐ก๐ ๐กโ๐๐น๐๐๐ข๐๐๐ข๐๐๐๐,๐๐๐Kc$is the Keulegan-Carpenter.
4. Result and Discussion
4.1 Development of scour
Similar to how the physical model was used, this numerical model was also used. The numerical model’s boundary conditions and other crucial variables that directly influence the outcomes were applied (flow depth, median particle size (d50), and wave velocity). After the initial 0-300 s, the scour rate reduced as the scour holes grew quickly. The scour depths steadied for about 1800 seconds before reaching an asymptotic value. The findings of scour depth with time are displayed in Figure 6.
4.2 Features of scour
Early on (t=400s), the scour hole began to appear beneath the main column and then began to extend along the diagonal bracing connecting to the wall-facing pile. Gradually, the geography of the scour; of these results is similar to the experimental observations of Stahlmann [4] and Aminoroayaie Yamini et al. [1]. As the waves reached the tripod, there was an enhanced flow acceleration underneath the main column and the lower diagonal braces as a result of the obstructing effects of the structural elements. More particles are mobilized and transported due to the enhanced near-bed flow velocity, it also increases bed shear stress, turbulence, and scour at the site. In comparison to a single pile, the main column and structural components of the tripod have a significant impact on the flow velocity distribution and, consequently, the scour process and morphology. The main column and seabed are separated by a gap, therefore the flow across the gap may aid in scouring. The scour hole first emerged beneath the main column and subsequently expanded along the lower structural components, both Aminoroayaie Yamini et al. [1] and Stahlmann [4] made this claim. Around the tripod, there are several different scour morphologies and the flow velocity distribution as shown in Figures 7 and 8.
Figure 8. Random waves of flow velocity distribution around a tripod
4.3 Wave velocity’s (Vw) impact on scour depth
In this study’s section, we looked at how variations in wave current velocity affected the scouring depth. Bed scour pattern modification could result from an increase or decrease in waves. As a result, the backflow area produced within the pile would become stronger, which would increase the depth of the sediment scour. The quantity of current turbulence is the primary cause of the relationship between wave height and bed scour value. The current velocity has increased the extent to which the turbulence energy has changed and increased in strength now present. It should be mentioned that in this instance, the Jon swap spectrum random waves are chosen. The scour depth attains its steady-current value for Vw<0.75, Figure 9 (a) shows that effect. When (V) represents the mean velocity=0.5 m.s-1.
Figure 9. Main effects on maximum scour depth (Smax) as a function of column diameter (D)
4.4 Impact of a median particle (d50) on scour depth
In this section of the study, we looked into how variations in particle size affected how the bed profile changed. The values of various particle diameters are defined in the numerical model for each run numerical modeling, and the conditions under which changes in particle diameter have an impact on the bed scour profile are derived. Based on Figure 9 (b), the findings of the numerical modeling show that as particle diameter increases the maximum scour depth caused by wave contact decreases. When (d50) is the diameter of Sediment (d50). The Shatt Al-Arab soil near Basra, Iraq, was used to produce a variety of varied diameters.
4.5 Impact of wave height and flow depth (h) on scour depth
One of the main elements affecting the scour profile brought on by the interaction of the wave and current with the piles of the wind turbines is the height of the wave surrounding the turbine pile causing more turbulence to develop there. The velocity towards the bottom and the bed both vary as the turbulence around the pile is increased, modifying the scour profile close to the pile. According to the results of the numerical modeling, the depth of scour will increase as water depth and wave height in random waves increase as shown in Figure 9 (c).
4.6 Froude number’s (Fr) impact on scour depth
No matter what the spacing ratio, the Figure 9 shows that the Froude number rises, and the maximum scour depth often rises as well increases in Figure 9 (d). Additionally, it is crucial to keep in mind that only a small portion of the findings regarding the spacing ratios with the smallest values. Due to the velocity acceleration in the presence of a larger Froude number, the range of edge scour downstream is greater than that of upstream. Moreover, the scouring phenomena occur in the region farthest from the tripod, perhaps as a result of the turbulence brought on by the collision of the tripod’s pile. Generally, as the Froude number rises, so does the deposition height and scour depth.
4.7 Keulegan-Carpenter (KC) number
The geography of the scour is significantly more influenced by the KC value. Greater KC causes a deeper equilibrium scour because an increase in KC lengthens the horseshoe vortex’s duration and intensifies it as shown in Figure 10.
The result can be attributed to the fact that wave superposition reduced the crucial KC for the initiation of the scour, particularly under small KC conditions. The primary variable in the equation used to calculate This is the depth of the scouring hole at the bed. The following expression is used to calculate the Keulegan-Carpenter number:
Kc=VwโTpD๐พ๐=๐๐คโ๐๐๐ท (13)
where, the wave period is Tp and the wave velocity is shown by Vw.
Figure 10. Relationship between the relative maximum scour depth and KC
5. Conclusion
(1) The existing seabed-tripod-fluid numerical model is capable of faithfully reproducing the scour process and the flow field around tripods, suggesting that it may be used to predict the scour around tripods in random waves.
(2) Their results obtained in this research at various flow velocities and flow depths demonstrated that the maximum scour depth rate depended on wave height with rising velocities and decreasing particle sizes (d50).
(3) A diagonal brace and the main column act as blockages, increasing the flow accelerations underneath them. This raises the magnitude of the disturbance and the shear stress on the seafloor, which in turn causes a greater number of particles to be mobilized and conveyed, as a result, causes more severe scour at the location.
(4) The Froude number and the scouring process are closely related. In general, as the Froude number rises, so does the maximum scour depth and scour range. The highest maximum scour depth always coincides with the bigger Froude number with the shortest spacing ratio.
Since the issue is that there aren’t many experiments or studies that are relevant to this subject, therefore we had to rely on the monopile criteria. Therefore, to gain a deeper knowledge of the scouring effect surrounding the tripod in random waves, further numerical research exploring numerous soil, foundation, and construction elements as well as upcoming physical model tests will be beneficial.
Nomenclature
CFD
Computational fluid dynamics
FAVOR
Fractional Area/Volume Obstacle Representation
VOF
Volume of Fluid
RNG
Renormalized Group
OWTs
Offshore wind turbines
Greek Symbols
ฮต, ฯ
Dissipation rate of the turbulent kinetic energy, m2s-3
Subscripts
d50
Median particle size
Vf
Volume fraction
GT
Turbulent energy of buoyancy
KT
Turbulent velocity
PT
Kinetic energy of the turbulence
ฮi
Induction parameter
ns
Induction parameter
ฮฮcr
The essential Shields variable
Di
Diameter of sediment
dโ
The diameter of particles without dimensions
ยตf
Dynamic viscosity of the fluid
qb,i
The bed load transportation rate
Cs,i
Sand particle’s concentration of mass
D
Diameter of pile
Df
Diffusivity
D
Diameter of main column
Fr
Froud number
Kc
KeuleganโCarpenter number
G
Acceleration of gravity g
H
Flow depth
Vw
Wave Velocity
V
Mean Velocity
Tp
Wave Period
S
Scour depth
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This paper conducts a three-dimensional numerical analysis on the surges generated by landslides of different water entry scales, and analyzes the characteristics of surge disasters induced by landslides of different water entry scales, such as surge height, surge speed, and bank climbing height. Meanwhile, the impact of surges caused by landslides of different water entry scales on the dam is explored.
The FLOW-3D numerical simulation method is employed to simulate and analyze the entire process of landslide instability, surge formation and propagation, surge climbing, and surge backflow. The results show that the maximum climbing height of the surge generated by the 3. 1 million m~3 landslide of water entry is 54. 5 m on the opposite bank, and the surge height in front of the dam is 6. 69 m.
The surge has a small area of overflow at the right bank dam shoulder. The surge generated by the 0. 8 million m~3 landslide of water entry has a maximum climbing height of 26. 00 m on the opposite bank, and the surge height in front of the dam is 5. 38 m, without influence exerted by the surge on the dam safety. The results indicate that the induced surge caused by 3. 1ร10~6 m~3 landslide of water entry is more catastrophic than that brought by 0. 8ร10~6 m~3 landslide of water entry.
Difference Analysis of Wave Disaster Characteristics Induced by Landslides of Different Water Entry Scales
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