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28 pages, 1662 KiB  
Review
Numerical Simulation of Earthquake Impacts on Marine Structures: A Comprehensive Review
by Adel Kabi, Jersson X. Leon-Medina and Francesc Pozo
Buildings 2024, 14(12), 4039; https://doi.org/10.3390/buildings14124039 - 19 Dec 2024
Viewed by 316
Abstract
Marine and underwater structures, such as seawalls, piers, breakwaters, and pipelines, are particularly susceptible to seismic events. These events can directly damage the structures or destabilize their supporting soil through phenomena like liquefaction. This review examines advanced numerical modeling approaches, including CFD, FEM, [...] Read more.
Marine and underwater structures, such as seawalls, piers, breakwaters, and pipelines, are particularly susceptible to seismic events. These events can directly damage the structures or destabilize their supporting soil through phenomena like liquefaction. This review examines advanced numerical modeling approaches, including CFD, FEM, DEM, FVM, and BEM, to assess the impacts of earthquakes on these structures. These methods provide cost-effective and reliable simulations, demonstrating strong alignment with experimental and theoretical data. However, challenges persist in areas such as computational efficiency and algorithmic limitations. Key findings highlight the ability of these models to accurately simulate primary forces during seismic events and secondary effects, such as wave-induced loads. Nonetheless, discrepancies remain, particularly in capturing energy dissipation processes in existing models. Future advancements in computational capabilities and techniques, such as high-resolution DNS for wave–structure interactions and improved near-field seismoacoustic modeling show potential for enhancing simulation accuracy. Furthermore, integrating laboratory and field data into unified frameworks will significantly improve the precision and practicality of these models, offering robust tools for predicting earthquake and wave impacts on marine environments. Full article
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Figure 1
<p>(<b>a</b>) Hull with transverse stiffeners CAD detail, (<b>b</b>) Preparation of mesh and for a hull with transverse stiffeners and (<b>c</b>) result of the vibration mode of the hull transversely stiffened at frequency 11.209 Hz [<a href="#B17-buildings-14-04039" class="html-bibr">17</a>].</p>
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<p>CFD-DEM simulation of particle ejection test. (<b>a</b>) Setup and (<b>b</b>) particle motion trajectory with and without Magnus force [<a href="#B21-buildings-14-04039" class="html-bibr">21</a>].</p>
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<p>Marine current turbine. Wake geometry of IBEM model at different operating conditions. From left to right, TSR = 3, 6, 9. The diameter of the turbine was 700 mm [<a href="#B27-buildings-14-04039" class="html-bibr">27</a>].</p>
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<p>Schematic of numerical wave tank: (<b>a</b>) cross-section and (<b>b</b>) plan view [<a href="#B31-buildings-14-04039" class="html-bibr">31</a>].</p>
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<p>(<b>a</b>) STL files for the bottom geometry and cylinder, and (<b>b</b>) Computational domain with bottom slope and vertical cylinder [<a href="#B31-buildings-14-04039" class="html-bibr">31</a>]. The dimensions correspond to those described in <a href="#buildings-14-04039-f004" class="html-fig">Figure 4</a>.</p>
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<p>Results of waves2Foam simulations in four time steps from 31.10 s, until 31.90 s [<a href="#B31-buildings-14-04039" class="html-bibr">31</a>].</p>
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<p>Computational domain and coordinate system for DNS of wind over steep and breaking waves [<a href="#B36-buildings-14-04039" class="html-bibr">36</a>]. (<b>a</b>) 3D View of the waves, (<b>b</b>) 2D view dash line shows the level <math display="inline"><semantics> <mrow> <mi>z</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> and red line indicate the wave.</p>
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<p>Beach profiles at Pont del Petroli. The original beach profile from the design report is indicated by a blue line. In red, the two profiles surveyed by LIM/UPC before and after storm Gloria [<a href="#B39-buildings-14-04039" class="html-bibr">39</a>].</p>
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<p>2D view of a pipe inside the lattice Boltzmann grid points [<a href="#B43-buildings-14-04039" class="html-bibr">43</a>].</p>
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20 pages, 11251 KiB  
Article
Dramatic Enhancement of Macrozoobenthic Species β-Diversity in Response to Artificial Breakwater Construction Along a Tropical Coastline
by Huan Chiao Lee, Christopher J. Glasby, Anja Schulze, Han Raven, Siong Kiat Tan, Takaomi Arai, Amirah Md Jin, Nurun Nazihah Tal’ah, Ainina Zarifi and David J. Marshall
Diversity 2024, 16(12), 742; https://doi.org/10.3390/d16120742 - 30 Nov 2024
Viewed by 595
Abstract
The beneficial or detrimental effects of human-built marine structures (piers, breakwaters, and seawalls) on macrozoobenthic assemblages and diversities are currently underexplored. The present study investigated the enhancement of β-diversity of oysterbed-associated species on breakwaters constructed along sandy beaches. We compared habitat complexities and [...] Read more.
The beneficial or detrimental effects of human-built marine structures (piers, breakwaters, and seawalls) on macrozoobenthic assemblages and diversities are currently underexplored. The present study investigated the enhancement of β-diversity of oysterbed-associated species on breakwaters constructed along sandy beaches. We compared habitat complexities and species assemblages among artificial breakwater shores (ABS), a natural rocky shore (NS), and an embayment shore (ES). Oysterbed habitat complexity was found to be greatest on the ABS due to the successional colonization of the reef-forming estuarine oyster, Saccostrea echinata, followed by the colonization of boring bivalves and burrowing annelids. High-resolution taxonomic data revealed that the ABS supports the greatest species richness, including 48.1% unique species and 33.3% species shared with the embayment shore. The other shores uniquely or in combination with ABS support up to 11.1% of the total species richness associated with the oysterbeds (n = 81). Taxonomic dominance in terms of species number was Mollusca > Annelida > Arthropoda. This study reveals that ABS enhances β-diversity by ~91% (Jaccard dissimilarity index), which is driven by the sequential cascading events of (1) sheltering of shores, (2) colonization of novel habitat-forming oysters, (3) novel macrozoobenthic species recruitment from adjacent shores and sheltered embayments, including habitat-forming bivalves and annelids, and (4) the recruitment of macrozoobenthic species to boreholes. ABS habitat complexity derives from a spatially distinct, three-tiered ecological engineering system, involving (1) breakwater construction (100 m), (2) reef-forming oysters (10 m), and (3) boring bivalves and burrowing annelids (<10 cm). Irrespective of the purpose of their construction, breakwaters along extended sandy shores can potentially increase the resilience (β-diversity) and regional interconnectivity of hard surface macrozoobenthic species. Full article
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<p>The predicted sequential temporal events associated with the oysterbed community on the breakwaters, the tiers of eco-engineering, and the relevant objectives to test these predictions.</p>
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<p>(<b>A</b>) Study locations along the South China Sea coastline of Brunei and the Brunei Bay, at Pantai Jerudong, Empire, Pantai Tungku, and Muara. (<b>B</b>) Satellite image showing extensive modification of the coastline, and the distribution of sandy beaches, natural rocky shores, and artificial breakwater shores (respectively, outlined in yellow, fuchsia, and cyan). Sampling locations are marked with colored circles. (<b>C</b>) Inner breakwater at Pantai Tungku, showing boulders (1–2 m<sup>3</sup>) and the establishment of oysterbeds (yellow arrows).</p>
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<p>Satellite images showing artificial breakwaters and a natural rocky shore. The distributions <span class="html-italic">Saccostrea echinata</span> beds (blue lines) and <span class="html-italic">Saccostrea mordax</span> beds (orange lines) at (<b>A</b>) Jerudong attached breakwater, (<b>B</b>) Tungku attached breakwater, (<b>C</b>) Tungku unattached breakwater, and (<b>D</b>) the natural rocky shore of Empire. Predicted direction and intensity of ocean currents indicated by gradational blue and white lines, with darker blue indicating strongest intensity eventually reduced to white. This study considered only (<b>A</b>,<b>B</b>,<b>D</b>).</p>
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<p>Oyster distributions and bed formation. (<b>A</b>) Scattered <span class="html-italic">Saccostrea mordax</span> at the natural rocky shore of Empire (NS). (<b>B</b>) Single-layered <span class="html-italic">Saccostrea mordax</span> bed at the Tungku breakwater (ABS). (<b>C</b>) Dense and stacked <span class="html-italic">Saccostrea echinata</span> bed at the Tungku breakwater (ABS).</p>
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<p>Section of <span class="html-italic">Saccostrea echinata</span> bed from an artificial breakwater viewed from (<b>A</b>) above, (<b>B</b>) side and (<b>C</b>) bottom. Successional settlement results in live (Live) and dead (Dead) oysters arranged vertically or horizontally within pile at the surface and middle layer. Crevices (Cr), boreholes (yellow arrows), and burrows (red arrow) can be observed within the pile and may be occupied by borers or nonborers. Fauna, such as bivalves (Bi), gastropod (Ga), barnacles (Ba), and limpets (Li), are indicated by white arrows. Bioeroded oyster shells (sh) and sediment (sd) are observed at the rocky substratum and become reconsolidated and compacted at the bottommost layer (red outlines).</p>
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<p>Section of <span class="html-italic">Saccostrea echinata</span> bed from the embayment viewed from (<b>A</b>) above, (<b>B</b>) side and (<b>C</b>) bottom. Live and dead oysters are arranged vertically or horizontally within the pile, which is thinner and less complex than that of the breakwater in <a href="#diversity-16-00742-f005" class="html-fig">Figure 5</a>A,B. No boreholes are observed. Oyster and barnacle shells are intact at the rocky substratum and have yet to be bioeroded and reconsolidated at the bottommost layer (see <a href="#diversity-16-00742-f005" class="html-fig">Figure 5</a>C). Live barnacles (Ba) indicated by white arrows.</p>
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<p>Species number associated with oysterbeds (<b>A</b>) grouped by phylum (<b>B</b>) at a combination of localities, ABS—breakwaters, NS—natural shore, and ES—embayment.</p>
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<p>A selection of species associated with artificial breakwater oysterbeds (stars indicate species unique to the artificial breakwaters). (1) <span class="html-italic">Leiosolenus malaccanus</span>, (2) <span class="html-italic">Neotrapezium sublaevigatum</span>, (3) <span class="html-italic">Botula</span> cf <span class="html-italic">cinnamomea</span>, (4) <span class="html-italic">Brachidontes crebristriatus</span>, (5) <span class="html-italic">Brachidontes variabilis</span>, (6) <span class="html-italic">Septifer excisus</span>, (7) <span class="html-italic">Septifer bilocularis</span>, (8) <span class="html-italic">Petricola divergens</span>, (9) <span class="html-italic">Irus macrophylla</span>, (10) <span class="html-italic">Isognomon nucleus</span>, (11) <span class="html-italic">Isognomon legumen</span>, (12) Actiniidae sp. 1, (13) <span class="html-italic">Cryptopilumnus changensis</span>, (14) <span class="html-italic">Heteropanope glabra</span>, (15) <span class="html-italic">Pachygrapsus minutus</span>, (16) <span class="html-italic">Metopograpsus frontalis</span>, (17) <span class="html-italic">Nanosesarma minutum</span>, (18) <span class="html-italic">Patelloida pygmaea</span>, (19) <span class="html-italic">Cellana radiata</span>, (20) <span class="html-italic">Montfortula</span> sp., (21) <span class="html-italic">Tenguella musiva</span>, (22) <span class="html-italic">Littoraria articulata</span>, (23) <span class="html-italic">Nerita chamaeleon</span>, (24) <span class="html-italic">Squamopleura miles</span>, (25) <span class="html-italic">Acanthochitona</span> sp. 1, (26) <span class="html-italic">Acanthochitona</span> sp. 2, (27) <span class="html-italic">Tetraclita kuroshioensis</span>, (28) <span class="html-italic">Balanus amphitrite</span>, (29) <span class="html-italic">Ibla cumingi</span>, (30) <span class="html-italic">Themiste lageniformis</span>, (31) <span class="html-italic">Antillesoma</span> sp., (32) <span class="html-italic">Phascolosoma scolops</span>, (33) <span class="html-italic">Eunice</span> sp., (34) <span class="html-italic">Lysidice</span> sp., (35) Hesionidae sp., (36) <span class="html-italic">Omobranchus obliquus</span>, (37) <span class="html-italic">Omobranchus elongatus</span>, (38) <span class="html-italic">Ecsenius trilineatus</span>, (39) <span class="html-italic">Laiphognatus multimaculatus</span>, (40) <span class="html-italic">Istiblennius dussumieri</span>, and (41) <span class="html-italic">Praealticus striatus</span>.</p>
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<p>nMDS based on presence/absence data of species associated with oysterbeds from the three shore types.</p>
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36 pages, 10546 KiB  
Article
Shore-Side Downfall Pressures Due to Waves Impacting a Vertical Seawall: An Experimental Study
by Annelie Baines, Lee S. Cunningham and Benedict D. Rogers
J. Mar. Sci. Eng. 2024, 12(12), 2149; https://doi.org/10.3390/jmse12122149 - 25 Nov 2024
Viewed by 539
Abstract
As part of an investigation into downfall impacts from violent overtopping waves, experimental data are presented for the impact pressures and forces generated by regular and focused waves breaking onto a vertical wall and impacting a landward horizontal deck at a scale of [...] Read more.
As part of an investigation into downfall impacts from violent overtopping waves, experimental data are presented for the impact pressures and forces generated by regular and focused waves breaking onto a vertical wall and impacting a landward horizontal deck at a scale of 1:38. Particular attention is given to the wave-by-wave uprush and impact downfall events. By selecting regular and focused wave conditions that produce impacts, new trends are identified for violent downfall phenomena that could easily be underestimated in current practice. The characteristics of the downfall impacts are investigated and three different types of downfall impact are identified and discussed. Using a Wavelet Filter to denoise the signal from pressure probes without losing the peak impact pressures or introducing a phase shift, the distinctive features and dynamic behaviours of the white-water impacts are considered, and it is shown that downfall pressure magnitudes of 3040 ρgH are regularly achieved. Dynamic impulse times of the events are also presented with higher-impact events generally relating to shorter impulse times, highlighting the dynamic character of these impacts. The largest downfall pressures are found to occur further from the vertical wall than previously measured. Importantly, the spray travelling furthest from the point of the initial wave impact on the vertical wall causes some of the largest downfall pressures on the deck. The paper concludes that, while the dataset is small, there are strong indications that the effects of these types of impacts are structurally significant and present a risk to infrastructure located landward of seawalls. Full article
(This article belongs to the Section Coastal Engineering)
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<p>Breaking waves at a vertical seawall, Norbreck, Blackpool, UK, 13 November 2020: plume formation (<b>top</b>), resulting downfall on landward deck (<b>bottom</b>). Droplet dispersal is clearly evident.</p>
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<p>Stages of spray formation (from Case H4T2 introduced later): (<b>a</b>) Sheet formation directly after wave impact. (<b>b</b>) Sheet breakup, with the heavier elements starting to fall back towards the structure. (<b>c</b>) Droplet breakup: separation of the droplets from the remaining sheet. (<b>d</b>) Droplet downfall and impact on deck.</p>
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<p>Schematic of Experimental Set-up, Plan (<b>top</b>), Section (<b>bottom</b>).</p>
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<p>Sketch of the model (not to scale): (<b>a</b>) side view, (<b>b</b>) front of structure viewed from offshore showing probes PF1, PF2, PF3, and (<b>c</b>) plan view of deck probes. Pressure probes in use are shown in green. Locations in red denote probe locations that were sealed using PVC stoppers.</p>
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<p>The University of Manchester wave flume. (<b>a</b>) Side view with beach in situ. (<b>b</b>) View of flume from wavemaker. (<b>c</b>) Model structure with pressure probes arrangement.</p>
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<p>Wavelet Filter vs. Fourier Transform filter. (<b>a</b>) Raw measured signal. (<b>b</b>) Low Pass FFT filter at 20 Hz. (<b>c</b>) Fifth order Wavelet Filter. Forces are unscaled.</p>
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<p>Three consecutive waves’ time-histories from H4T2 (<b>a</b>) Vertical wall impact pressures (PF1, PF2, PF3); (<b>b</b>) Horizontal deck impact pressures (PD12, PD13, PD23, PD33, PD32); and (<b>c</b>) Measured surface-elevation.</p>
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<p>Typical profile type 1 from H4T2. Higher impact pressure associated with a lower downfall pressure. <b>Left</b>: vertical pressure–time profile, <b>right</b>: deck pressure–time profile.</p>
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<p>Typical profile type 2 from H4T2. Low impact pressure associated with higher downfall pressure. <b>Left</b>: vertical pressure–time profile, <b>right</b>: deck pressure–time profile.</p>
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<p>Typical profile type 3 from H4T2. Long dynamic impulse on deck (PD23). <b>Left</b>: vertical pressure–time profile, <b>right</b>: deck pressure–time profile.</p>
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<p>Peak recorded Face Pressures (FP1, FP2 and FP3) for each wave plotted with the corresponding Peak recorded Deck Pressures for PD12, PD13, PD23, PD33, and PD32 separated by wave height for T2, coloured by deck pressure probes. (<b>a</b>) H1T2, (<b>b</b>) H2T2, (<b>c</b>) H3T2, (<b>d</b>) H4T2, (<b>e</b>) H5T2, (<b>f</b>) H6T2, (<b>g</b>) H7T2.</p>
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<p>Diagram of the identification of the dynamic rise time. Solid line: Filtered pressure using Wavelet Filter Dashed: 20 Hz Fourier Filter applied to the Wavelet filtered results. Circles: intercepts identified as start and end of dynamic impulse.</p>
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<p>Normalised pressures on the deck plotted against the time of the dynamic impact in ms for T4 cases.</p>
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<p>Normalised pressures on the deck plotted against the normalised pressure probe position, <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>/</mo> <msub> <mrow> <mi>H</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </mrow> </semantics></math>, for each wave height. Dashed line on each plot represents the location of the first row of probes, which were not used in the final tests shown here. Separated by wave height (T2) (<b>a</b>) H1T2, (<b>b</b>) H2T2, (<b>c</b>) H3T2, (<b>d</b>) H4T2, (<b>e</b>) H5T2, (<b>f</b>) H6T2, and (<b>g</b>) H7T2.</p>
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<p>Free-surface elevation for R1 to R5 (test series FG1), superimposed for WG1.</p>
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<p>Pressure–time plots for face pressures for R2, R3, R4 (repetition 2, 3, and 4) of FG3, superimposed for PF1.</p>
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<p>Pressure–time plots for deck pressures for R2, R3, and R4 of FG3, superimposed and separated by pressure probe: (<b>a</b>) PD12, (<b>b</b>) PD13, (<b>c</b>) PD32, and (<b>d</b>) PD33.</p>
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<p>Typical profile type 1 (FG1) at T = 26.5 s <b>Left</b>: Face pressure at PF1, <b>Right</b>: Deck impact pressure profile showing PD12, PD13, PD33, and PD32.</p>
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<p>Typical profile type 2 (FG1) at T = 217.2 s <b>Left</b>: Face pressure at PF1, <b>Right</b>: Deck impact pressure profile showing PD12, PD13, PD33, and PD32.</p>
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<p>Typical profile type 3 (FG1) at T = 153.4 s. <b>Left</b>: Face pressure at PF1, <b>Right</b>: Deck impact pressure profile showing PD12, PD13, PD33, and PD32.</p>
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<p>Images captured of the peak wave of the focused group FG1 (<b>a</b>,<b>b</b>) plunging wave breaking at the focal point (toe of beach). (<b>c</b>) plunging wave toe impacting with structure. (<b>d</b>–<b>f</b>) Stages of spray formation: (<b>d</b>) Sheet formation directly after wave impact. (<b>e</b>) Sheet breakup, with the heavier elements starting to fall back towards the structure. (<b>f</b>) Droplet breakup: separation of the droplets from the remaining sheet.</p>
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18 pages, 26956 KiB  
Article
Dynamic Response Study of Coral Reef Revetment Project Under Extreme Wave Action
by Jielong Hu, Songgui Chen, Hanbao Chen, Zhichao Nie, Zuoda Qi and Zihao Duan
Sustainability 2024, 16(22), 9939; https://doi.org/10.3390/su16229939 - 14 Nov 2024
Viewed by 501
Abstract
It is crucial for reef revetments to respond dynamically to rigorous wave actions for structural stability and safety. A comprehensive analysis of the interaction between the wave force and wave overtopping in a reef revetment project was conducted based on wave flume experiments. [...] Read more.
It is crucial for reef revetments to respond dynamically to rigorous wave actions for structural stability and safety. A comprehensive analysis of the interaction between the wave force and wave overtopping in a reef revetment project was conducted based on wave flume experiments. This study explored how wave conditions, the water depth along the reef flat, and the proximity of the reef edge to the revetment project influenced wave overtopping and wave force patterns. The results indicate that as the incident wave height, period, and water depth along the reef flat increased, the average wave overtopping within the revetment project also increased. Additionally, higher levels of average wave overtopping occurred with the decrease in the distance between the revetment project and the reef edge. The peak wave force on the seawall of the revetment project was studied in response to various factors, including wave period, wave height, water depth along the reef flat, and distance to the reef edge. The changes in the maximum wave force reflected those of the average wave overtopping, with a strong linear correlation. The quantitative relationship between these variables was determined, and the wave forces on the seawall could be indirectly estimated using the average wave overtopping volume. This study provides an efficient methodology for assessing the dynamic attributes of revetment projects and the disaster risk of these structures. Full article
(This article belongs to the Special Issue Critical Issues in Ocean and Coastal Engineering)
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<p>Wave flume (68 m × 1 m × 1.5 m).</p>
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<p>Schematic diagram of revetment project structure (unit: m).</p>
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<p>Experimental arrangement (unit: m).</p>
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<p>Pressure sensor layout diagram (unit: cm).</p>
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<p>Average overtopping amount at location 1 of the revetment project at freeboard heights of (<b>a</b>) 9 m; (<b>b</b>) 7.5 m; and (<b>c</b>) 6 m.</p>
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<p>Average overtopping amount at location 2 of the revetment project at freeboard heights of (<b>a</b>) 9 m; (<b>b</b>) 7.5 m; and (<b>c</b>) 6 m.</p>
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<p>The influence of freeboard height on the average overtopping amount of revetment project.</p>
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<p>The influence of revetment project location on the average overtopping amount.</p>
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<p>The impact of wave steepness on the dimensionless average overtopping volume (<b>a</b>) Rc = 9 m; (<b>b</b>) Rc = 6 m.</p>
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<p>Effect of relative freeboard height on the dimensionless average overtopping volume (<b>a</b>) S = 75 m; (<b>b</b>) T = 17.43 s.</p>
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<p>Time series of wave pressure changes.</p>
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<p>The effect of wave height on wave pressure.</p>
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<p>The effect of wave period on wave pressure.</p>
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<p>The effect of freeboard height on wave pressure.</p>
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<p>The effect of the revetment project location on wave pressure.</p>
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<p>Relationship between dimensionless average wave overtopping volume and dimensionless wave force.</p>
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<p>Relationship between dimensionless average wave overtopping volume and dimensionless wave force.</p>
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<p>Comparison figure of Equation (2), Molines’ formula and experimental values.</p>
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16 pages, 7298 KiB  
Article
Experimental Study on Optimization of Consolidation Parameters of Silty Clay Based on Response Surface Methodology: A Case Study on the Protection and Restoration of the Ming and Qing Dynasty Hangzhou Seawall Site
by Liang Ye, Zhenyan Chen, Liquan Wu and Baoping Zou
Sustainability 2024, 16(18), 8219; https://doi.org/10.3390/su16188219 - 21 Sep 2024
Viewed by 872
Abstract
The preservation of the ancient seawall site is a focal point and challenge in the protection of historical relics along Hangzhou’s Grand Canal in China. This endeavor holds significant historical and contemporary value in uncovering and perpetuating Hangzhou’s cultural heritage. Researchers investigating the [...] Read more.
The preservation of the ancient seawall site is a focal point and challenge in the protection of historical relics along Hangzhou’s Grand Canal in China. This endeavor holds significant historical and contemporary value in uncovering and perpetuating Hangzhou’s cultural heritage. Researchers investigating the Linping section of the seawall site aimed to address soil site deterioration by selecting environmentally friendly alkali-activated slag cementitious materials and applying the response surface method (RSM) to conduct solidification experiments on the seawall soil. Researchers used the results of unconfined compressive strength tests and microscopic electron microscopy analysis, considering the comprehensive performance of soil solidification mechanisms and mechanical properties, to establish a least-squares regression fitting model to optimize the solidification material process parameters. The experimental results indicate that the optimal mass ratio of lime, gypsum, and slag for achieving the best solidification process parameters for the seawall soil, with a 28-day curing period, is 1:1.9:6.2. This ratio was subsequently applied to the restoration and reconstruction of the seawall site, with parts of the restored seawall exhibited in a museum to promote the sustainable conservation of urban cultural heritage. This study provides theoretical support and practical guidance for the protection and restoration of soil sites. Full article
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<p>Photographs of the Linping section of the Hangzhou seawall site.</p>
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<p>Schematic diagram of the composition points for the experimental group in the central composite circumscribed design.</p>
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<p>Response surface plot (<b>a</b>) and contour plot (<b>b</b>) of compressive strength for the lime and gypsum interaction.</p>
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<p>Response surface plot (<b>a</b>) and contour plot (<b>b</b>) of compressive strength for the slag and lime interaction.</p>
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<p>Response surface plot (<b>a</b>) and contour plot (<b>b</b>) of compressive strength for the slag and gypsum interaction.</p>
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<p>Morphology of the original soil from the seawall site observed using a scanning electron microscope (SEM).</p>
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<p>Microstructure of the 28-day solidified soil sample at 250× magnification.</p>
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<p>Microstructure of the 28-day solidified soil sample at 400× magnification.</p>
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<p>Pareto chart of standardized effects on 28-day compressive strength.</p>
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<p>Preliminary replica model of the seawall site.</p>
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<p>Exhibited model of the seawall site of Hangzhou in the museum: (<b>a</b>) Located in the Museum of the Seawall Site of Hangzhou; (<b>b</b>) Located in the Hangzhou Museum.</p>
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20 pages, 9422 KiB  
Article
Interrelationship between Wall and Beach Erosion in Loc An, Vietnam: Remote Sensing and Numerical Modeling Approaches
by Dinh Van Duy, Nguyen Quang Duc Anh, Nguyen Trung Viet and Hitoshi Tanaka
Water 2024, 16(17), 2553; https://doi.org/10.3390/w16172553 - 9 Sep 2024
Viewed by 833
Abstract
Beach erosion and coastal protection are complex and interconnected phenomena that have a substantial impact on coastal environments worldwide. Among the various coastal protection measures, seawalls have been widely implemented to mitigate erosion and protect coastal assets. However, the interrelationship between beach erosion [...] Read more.
Beach erosion and coastal protection are complex and interconnected phenomena that have a substantial impact on coastal environments worldwide. Among the various coastal protection measures, seawalls have been widely implemented to mitigate erosion and protect coastal assets. However, the interrelationship between beach erosion and seawalls remains a critical topic for investigation to ensure effective and sustainable coastal management strategies. Seawalls impact the shoreline, particularly through the “end effect”, where the seawall functions similarly to a groin, causing erosion on the downdrift side relative to the direction of wave approach. This study provides a detailed analysis of the interplay between beach erosion and seawall structures in Loc An, Vietnam, employing both remote sensing and numerical approaches. Sentinel-2 images were employed together with an analytical solution to observe the shoreline change at the Loc An sand spit and to determine input values for the numerical model. Based on the shoreline dynamics, a numerical scheme was employed to study the shoreline evolution after the construction of a seawall. Our findings show that the shoreline evolution can be divided into three stages: (1) The first stage corresponds to the elongation of the sand spit without interference from coastal structures. (2) The second stage shows the effect of jetties on the shoreline, as signaled by the buildup of sand updrift of the jetties. (3) The third stage shows the effectiveness of the seawall, where the shoreline reaches its equilibrium condition. The study provides a quick and simple method for estimating shoreline diffusivity (ε) in situations where measured data is scarce. Full article
(This article belongs to the Section Oceans and Coastal Zones)
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<p>The location of the study area: Loc An sand spit, Ba Ria-Vung Tau province.</p>
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<p>Hourly water level collected at the Vung Tau Oceanographic station.</p>
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<p>The principle of the one-line model for shoreline change, as re-drawn based on the sketch mentioned in Duy et al. (2022) [<a href="#B19-water-16-02553" class="html-bibr">19</a>].</p>
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<p>The appearances of jetties and seawalls along the Loc An sand spit.</p>
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<p>Shoreline evolution from 2015 to 2023 of the Loc An sand spit.</p>
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<p>The three stages of shoreline evolution at the Loc An sand spit.</p>
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<p>Shoreline evolution on the updrift side of a groin, as re-drawn based on the sketch mentioned in Larson et al. (1987) [<a href="#B35-water-16-02553" class="html-bibr">35</a>].</p>
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<p>Transforming the images from the UTM system to the local coordinate system.</p>
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<p>The construction time of the jetties. The red-dashed circle highlights the jetty located at its center.</p>
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<p>Comparison between the measured shoreline and the modeled shorelines.</p>
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<p>RMSE between the modeled and measured shorelines.</p>
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<p>Validation of the analytical model.</p>
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<p>Shoreline evolution between two jetties, as re-drawn based on the sketch mentioned in Tanaka and Nadaoka (1982) [<a href="#B17-water-16-02553" class="html-bibr">17</a>].</p>
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<p>Shoreline evolution at the jetties in case of (<b>a</b>) one boundary and (<b>b</b>) two boundaries.</p>
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<p>Construction of the seawall.</p>
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<p>Comparison between modeled shorelines and measured shorelines.</p>
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<p>Evolution of the shoreline at the jetties (<span class="html-italic">x</span> = 960 m).</p>
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<p>Shoreline positions extracted at the jetties (<span class="html-italic">y</span><sub>1</sub>) before and after making tidal correction.</p>
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<p>Distribution of sediment grain size along the coast of Ba Ria–Vung Tau province, as re-produce based on the map mentioned in Duc Anh (2021) [<a href="#B5-water-16-02553" class="html-bibr">5</a>].</p>
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<p>Comparison of <span class="html-italic">ε</span> values between two methods.</p>
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20 pages, 7831 KiB  
Article
Beach Nourishment Protection against Storms for Contrasting Backshore Typologies
by Filipa S. B. F. Oliveira, André B. Fortunato and Paula Freire
J. Mar. Sci. Eng. 2024, 12(9), 1465; https://doi.org/10.3390/jmse12091465 - 23 Aug 2024
Viewed by 617
Abstract
The protection against a storm event provided by nourishment to Costa da Caparica beaches near Lisbon, Portugal, is investigated numerically with a two-dimensional-horizontal morphodynamic model able to generate and propagate the longer infragravity waves. The beach has a groyne field and a multi-typology [...] Read more.
The protection against a storm event provided by nourishment to Costa da Caparica beaches near Lisbon, Portugal, is investigated numerically with a two-dimensional-horizontal morphodynamic model able to generate and propagate the longer infragravity waves. The beach has a groyne field and a multi-typology backshore. The nourishment of 106 m3 of sand was placed at the beach face and backshore. Pre- and post-nourishment topo-bathymetric surveys of the beach, which suffers from chronic erosion, were performed under a monitoring program. The morphodynamics of the pre- and post-nourished beach when exposed to a simulated historically damaging storm event and the post-storm morphologies were compared to evaluate the efficacy of the nourishment. Results indicate that the lower surface level of the beach face and backshore of the pre-nourished beach induces a larger erosion volume. The nourishment prevented the extreme retreat of the shoreline that occurred during the storm in the pre-nourished beach and reduced the storm-induced erosion volume by 20%, thus protecting the beach effectively against the storm. The beach backshore typology (seawall vs. dune) exerts differential influences on the sandy bottom. As a result, multi-typology backshores induce alongshore variability in cross-shore dynamics. The backshore seawalls exposed to direct wave action cause higher erosion volumes and a larger cross-shore extension of the active zone. The most vulnerable alongshore sectors of the beach were identified and related to the mechanisms responsible for the erosion phenomenon. These findings strengthen the importance of sand nourishment for the protection and sustainability of beaches, particularly those with a seawall at the backshore, where storm events cause higher erosion. Full article
(This article belongs to the Section Coastal Engineering)
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<p>Location of Costa da Caparica (west coast of Portugal, Europe), with place names, topo-bathymetry of the Tagus Estuary (color gradient scale), and coastal depth contours 8, 16, and 30 m (adapted from <a href="https://geomar.hidrografico.pt/" target="_blank">https://geomar.hidrografico.pt/</a>, on 8 April 2024).</p>
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<p>Digital terrain models of the topo-bathymetric surveys of July–August 2008 (<b>a</b>) and November 2008 (<b>b</b>).</p>
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<p>Scheme of the numerical models applied.</p>
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<p>Spatial distribution of the 10<sup>6</sup> m<sup>3</sup> of sand nourishment performed in August 2008 (∆Z &gt; 0: accretion; ∆Z &lt; 0: erosion).</p>
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<p>Significant wave height, Hs, in the first fortnight of January 2014: records of Leixões and Sines (at north and south respectively) buoys and WaveWatch III model results in the location of the buoys and offshore Costa da Caparica.</p>
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<p>Hydrodynamics at the entrance (northwest, middle, and southeast positions of the offshore boundary of the numerical domain) of the morphodynamic model (results of the intermediate scale model) during the storm Hercules: (<b>a</b>) sea level; (<b>b</b>) significant wave height (Hs); (<b>c</b>) peak period (Tp); and (<b>d</b>) mean wave direction (Dir).</p>
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<p>Comparison of the topo-bathymetric surveys of August 2014 and October 2014 and the location of the shore-normal profiles PCC3, PCC5, PCC7, PCC9, PCC11, and PCC14.</p>
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<p>Numerical and observed evolution of the shore-normal profiles (<b>a</b>) PCC3, (<b>b</b>) PCC5, (<b>c</b>) PCC7, (<b>d</b>) PCC9, (<b>e</b>) PCC11, and (<b>f</b>) PCC14, between August 2014 and October 2014.</p>
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<p>Numerical and observed evolution of the shore-normal profiles (<b>a</b>) PCC3, (<b>b</b>) PCC5, (<b>c</b>) PCC7, (<b>d</b>) PCC9, (<b>e</b>) PCC11, and (<b>f</b>) PCC14, between August 2014 and October 2014.</p>
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<p>Site view with the location of the inspection profiles (<b>a</b>). Results of the morphological changes in Costa da Caparica during the Hercules storm: evolution over the pre-nourished topo-bathymetry (<b>b</b>), and evolution over the post-nourished topo-bathymetry (<b>c</b>).</p>
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<p>Erosion and accretion volumes in the cells between groynes for the pre- and post-nourishment cases.</p>
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<p>Results of the morphological changes in the eleven cross-shore inspection profiles, (<b>a</b>) X = 50, (<b>b</b>) X = 100, (<b>c</b>) X = 150, (<b>d</b>) X = 250, (<b>e</b>) X = 300, (<b>f</b>) X = 350, (<b>g</b>) X = 450, (<b>h</b>) X = 500, (<b>i</b>) X = 550, (<b>j</b>) X = 600, and (<b>k</b>) X = 650, for the pre- and post-nourishment cases.</p>
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<p>Results of the morphological changes in the eleven cross-shore inspection profiles, (<b>a</b>) X = 50, (<b>b</b>) X = 100, (<b>c</b>) X = 150, (<b>d</b>) X = 250, (<b>e</b>) X = 300, (<b>f</b>) X = 350, (<b>g</b>) X = 450, (<b>h</b>) X = 500, (<b>i</b>) X = 550, (<b>j</b>) X = 600, and (<b>k</b>) X = 650, for the pre- and post-nourishment cases.</p>
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<p>Erosion in the eleven inspection profiles for the pre- and post-nourishment cases.</p>
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<p>Initial profiles X = 50, X = 100, and X = 350 for the pre- and post-nourishment cases.</p>
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<p>Results of the morphological changes: post-storm position of the 0 and +2m CD bathymetric lines for the pre- and post-nourishment cases.</p>
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23 pages, 16937 KiB  
Article
Study on the Characteristics of Flow over a Seawall and Its Impact on Pedestrians under Solitary Wave Action
by Yadong Hou, Xizeng Zhao, Gang Tao, Zhaoyuan Huang, Nanhui Xu and Zequan Leng
Water 2024, 16(16), 2357; https://doi.org/10.3390/w16162357 - 22 Aug 2024
Viewed by 1012
Abstract
In response to the incident of tourists falling into the sea due to waves on the seawall berm at Macau Road, Qingdao, during the passage of Typhoon “Songda” in 2022, a combination of numerical simulations and physical model experiments was performed to investigate [...] Read more.
In response to the incident of tourists falling into the sea due to waves on the seawall berm at Macau Road, Qingdao, during the passage of Typhoon “Songda” in 2022, a combination of numerical simulations and physical model experiments was performed to investigate the mechanics of the event, with emphasis on the wave flow characteristics and the flow evolution process on the seawall berm as well as the force exerted on a human body-equivalent cylinder model. The study found that the thickness of the return flow was significantly greater than that of the overtopping flow on the landward part of the berm. The recoil forces applied to the model on the berm were larger than the impact forces, and the ratio tended towards 1 as the wave height increased. In addition, the stability of pedestrians on the seawall berm was analyzed. The instability conditions for pedestrians in cross-wave flows differed slightly from those in floods. Full article
(This article belongs to the Special Issue Wave–Structure Interaction in Coastal and Ocean Engineering)
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<p>Typical landscaped sloping dikes.</p>
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<p>Two tourists were swept out to sea during Typhoon Songda on 31 July 2022.</p>
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<p>Schematic of physical wave tank. (<b>a</b>) Side view. (<b>b</b>) Top view. (<b>c</b>) Definition of relevant physical quantities.</p>
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<p>Schematic diagram of six-axis force sensors installation.</p>
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<p>Computational domain and mesh around the cylinder.</p>
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<p>Verification of grid convergence. (<b>a</b>) Wavefront pattern at WG1. (<b>b</b>) Thickness of water flow at the front edge of the berm of the dike. (<b>c</b>) Cross-sectional flow velocity at the front edge of the berm of the dike. (<b>d</b>) Cylinder force.</p>
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<p>Verification of grid convergence and comparison of numerical and physical modeling results. (<b>a</b>) Force verification. (<b>b</b>) Free level verification. (<b>c</b>) Thickness verification.</p>
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<p><span class="html-italic">d</span> = 0.46 m cylinder force verification. (<b>a</b>) <span class="html-italic">H</span> = 0.08 m. (<b>b</b>) <span class="html-italic">H</span> = 0.10 m. (<b>c</b>) <span class="html-italic">H</span> = 0.12 m.</p>
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<p>d = 0.42 m, H = 0.14 m. Thickness of water flow at different locations on the viewing platform.</p>
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<p>Thickness distribution along the berm of the dike cross-wave flow (<b>a</b>) <span class="html-italic">d</span> = 0.40 m; (<b>b</b>) <span class="html-italic">d</span> = 0.42 m.</p>
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<p>Relationship between thickness distribution along the return flow layer at the berm of the dike.</p>
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<p>Evolution of the wave current velocity profile at 0.1 m from the leading edge of the seawall.</p>
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<p>Evolution of wave return flow velocity profile at 0.1 m from the leading edge of the seawall.</p>
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<p><span class="html-italic">d</span> = 0.42 m, <span class="html-italic">H</span> = 0.14 m. velocity of water flow at different locations on the viewing platform.</p>
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<p><span class="html-italic">d</span> = 0.42 m. Relationships between flow velocity distribution in the impact flow layer at the berm of the dike.</p>
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<p>Relationship between flow velocity distribution along the return flow layer at the berm of the dike.</p>
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<p>Climbing process of over-wave flow.</p>
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<p>Wave reflux process.</p>
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<p>Historical force curves of the cylinder under different wave heights.</p>
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<p>Peak force on the cylinder at different locations. (<b>a</b>) <span class="html-italic">d</span> = 0.42 m peak impact forces; (<b>b</b>) <span class="html-italic">d</span> = 0.42 m peak recoil forces.</p>
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<p>d = 0.42 m. <span class="html-italic">U</span> <sup>2</sup><span class="html-italic">h</span> at different locations on the berm of the embankment. (<b>a</b>) <span class="html-italic">U</span> <sup>2</sup><span class="html-italic">h</span> time profile. (<b>b</b>) Peak value of <span class="html-italic">U</span> <sup>2</sup><span class="html-italic">h</span> during impact and return.</p>
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<p>The ratio of recoil forces to peak impact forces: (<b>a</b>) <span class="html-italic">d</span> = 0.40 m; (<b>b</b>) <span class="html-italic">d</span> = 0.42 m.</p>
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<p>Schematic diagram of human body forces under wave impacts.</p>
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<p>W at different water depths and wave heights. (<b>a</b>) Impact process. (<b>b</b>) Return process.</p>
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22 pages, 7491 KiB  
Article
Computational Study of Overtopping Phenomenon over Cylindrical Structures Including Mitigation Structures
by Gustavo A. Esteban, Xabier Ezkurra, Iñigo Bidaguren, Iñigo Albaina and Urko Izquierdo
J. Mar. Sci. Eng. 2024, 12(8), 1441; https://doi.org/10.3390/jmse12081441 - 20 Aug 2024
Viewed by 828
Abstract
Wave overtopping occurring in offshore wind renewable energy structures such as tension leg platforms (TLPs) or semi-submersible platforms is a phenomenon that is worth studying and preventing in order to extend the remaining useful life of the corresponding facilities. The behaviour of this [...] Read more.
Wave overtopping occurring in offshore wind renewable energy structures such as tension leg platforms (TLPs) or semi-submersible platforms is a phenomenon that is worth studying and preventing in order to extend the remaining useful life of the corresponding facilities. The behaviour of this phenomenon has been extensively reported for linear coastal defences like seawalls. However, no referenced study has treated the case of cylindrical structures typical of these applications to a similar extent. The aim of the present study is to define an empirical expression that portrays the relative overtopping rate over a vertical cylinder including a variety of bull-nose type mitigation structures to reduce the overtopping rate in the same fashion as for the linear structures characteristic of shoreline defences. Hydrodynamic interaction was studied by means of an experimentally validated numerical model applied to a non-impulsive regular wave regime and the results were compared with the case of a plain cylinder to evaluate the expected improvement in the overtopping performance. Four different types of parapets were added to the crest of the base cylinder, with different parapet height and horizontal extension, to see the influence of the geometry on the mitigation efficiency. Computational results confirmed the effectivity of the proposed solution in the overtopping reduction, though the singularity of each parapet geometry did not lead to an outstanding difference between the analysed options. Consequently, the resulting overtopping decrease in all the proposed geometries could be modelled by a unique specific Weibull-type function of the relative freeboard, which governed the phenomenon, showing a net reduction in comparison with the cylinder without the geometric modifications. In addition, the relationship between the reduced relative overtopping rate and the mean flow thickness over the vertical cylinder crest was studied as an alternative methodology to assess the potential damage caused by overtopping in real structures without complex volumetric measurements. The collection of computational results was fitted to a useful function, allowing for the definition of the overtopping discharge once the mean flow thickness was known. Full article
(This article belongs to the Section Ocean Engineering)
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<p>Main parameters that affect the overtopping phenomenon in a vertical wall including a parapet. (Original elaboration based on Figure 7.21 of <span class="html-italic">EurOtop</span> manual [<a href="#B6-jmse-12-01441" class="html-bibr">6</a>]).</p>
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<p>Overview of different overtopping regimes on vertical walls and cylinders [<a href="#B6-jmse-12-01441" class="html-bibr">6</a>,<a href="#B21-jmse-12-01441" class="html-bibr">21</a>,<a href="#B40-jmse-12-01441" class="html-bibr">40</a>,<a href="#B41-jmse-12-01441" class="html-bibr">41</a>,<a href="#B42-jmse-12-01441" class="html-bibr">42</a>].</p>
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<p>Visualisation of parapet geometries. The total height represented is the maximum crest freeboard. The axial-symmetric cross-section is represented.</p>
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<p>Exported flow rate signals: (<b>a</b>) instantaneous flow rate, (<b>b</b>) accumulated overtopped volume. (Case: <span class="html-italic">R<sub>c</sub></span>/<span class="html-italic">H</span> = 0.538, <span class="html-italic">H</span> = 0.13 m, Geometry 4).</p>
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<p>Exported flow thickness signals: (<b>a</b>) instantaneous flow thickness, (<b>b</b>) integrated value over time. (Case: <span class="html-italic">R<sub>c</sub></span>/<span class="html-italic">H</span> = 0.538, <span class="html-italic">H</span> = 0.13 m, Geometry 4).</p>
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<p>Computational domain of the numerical model.</p>
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<p>Mesh of the numerical wave flume: (<b>a</b>) general overview, (<b>b</b>) detailed view around the cylinder and the parapet and (<b>c</b>) detailed view above the crest.</p>
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<p>Initial conditions for free surface (<b>top</b>), velocity (<b>middle</b>) and pressure contours (<b>bottom</b>).</p>
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<p>Volume fraction of water at the symmetry plane and free surface shape evolution with time: (<b>a</b>–<b>c</b>) plain cylinder and (<b>d</b>–<b>f</b>) cylinder with parapet. Left: longitudinal symmetry plane; bottom: transversal symmetry plane; right: 3D view. (Relative freeboard <span class="html-italic">R<sub>c</sub></span>/<span class="html-italic">H</span> = 0.538, height <span class="html-italic">H</span> = 0.13 m, parapet geometry 4).</p>
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<p>Comparison of the evolution of the overtopping phenomenon with time for a cylinder with and without parapet: (<b>a</b>) instantaneous overtopping discharge, (<b>b</b>) accumulated overtopped volume, (<b>c</b>) instantaneous flow thickness and (<b>d</b>) flow thickness integrated over time. (Relative freeboard <span class="html-italic">R<sub>c</sub></span>/<span class="html-italic">H</span> = 0.538, height <span class="html-italic">H</span> = 0.13 m, parapet geometry 4).</p>
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<p>Relative overtopping rate as a function of relative freeboard of the parapet geometries: (<b>a</b>) Geometry 1, (<b>b</b>) Geometry 2, (<b>c</b>) Geometry 3 and (<b>d</b>) Geometry 4.</p>
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<p>Relative overtopping rate as a function of relative freeboard: (<b>a</b>) different regressions for each geometry; (<b>b</b>) common regression for all geometries.</p>
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<p>Correlation between computational and estimated results of the overtopping rate.</p>
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<p>Nondimensionalised mean flow thickness as a function of relative freeboard of the different parapet geometries (<b>a</b>) and overall tendency (<b>b</b>).</p>
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<p>Dependence of the relative overtopping rate on the nondimensionalised mean flow thickness: (<b>a</b>) fitting line and (<b>b</b>) quality of the fitting.</p>
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18 pages, 3543 KiB  
Article
Multi-Objective Optimization of the Seawall Cross-Section by DYCORS Algorithm
by Yuanyuan Tao and Pengzhi Lin
Water 2024, 16(16), 2222; https://doi.org/10.3390/w16162222 - 6 Aug 2024
Viewed by 881
Abstract
The purpose of this research is to develop a new method for automatically optimizing the seawall cross-section with composite slopes and a berm, considering both overtopping discharge and construction cost. Minimizing these competing multi-objectives is highly challenging due to the intricate geometry of [...] Read more.
The purpose of this research is to develop a new method for automatically optimizing the seawall cross-section with composite slopes and a berm, considering both overtopping discharge and construction cost. Minimizing these competing multi-objectives is highly challenging due to the intricate geometry of seawalls. In this study, the surrogate model optimization algorithm DYCORS (Dynamic COordinate search using Response Surface models) is employed to search for the optimal seawall geometry, coupled with the ANN (Artificial Neural Network) model for determining the overtopping discharge. A total of 20 trials have been run to evaluate the performance of our methodology. Even the worst-performing Trial 7 among these 20 trials shows a satisfactory performance, with a reduction of 17.67% in overtopping discharge and a 12.1% decrease in cost compared to the original solution. Furthermore, compared to other optimization schemes using GAs (Genetic Algorithms) with the same decision vectors, constraints, and multi-objective functions, the methodology has been proven to be more effective and robust. Additionally, when facing different combinations of wave conditions and water levels, there was a 27.8% reduction in objective function value compared to the original solution. The optimal results indicate that this method can still be effectively applied for optimizing the seawall cross-section as it is a general method. Full article
(This article belongs to the Section Oceans and Coastal Zones)
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<p>Flowchart of the methodology for the seawall cross-section optimization using the DYCORS algorithm.</p>
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<p>Cross-section sketch of the seawall with composite slopes and a berm in a coastal area of China.</p>
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<p>The configuration of a single-slope seawall with the upslope <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">α</mi> <mi mathvariant="normal">u</mi> </msub> </mrow> </semantics></math> (no berm).</p>
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<p>The configuration of a single-slope seawall with the upslope <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">α</mi> </mrow> <mrow> <mi mathvariant="normal">d</mi> </mrow> </msub> </mrow> </semantics></math> and wider crest width.</p>
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<p>The configuration of a single-slope seawall with the upslope <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">α</mi> </mrow> <mrow> <mi mathvariant="normal">u</mi> </mrow> </msub> </mrow> </semantics></math> = 1.5 (no berm).</p>
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<p>The configuration of a single-slope seawall with the upslope <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">α</mi> </mrow> <mrow> <mi mathvariant="normal">d</mi> </mrow> </msub> </mrow> </semantics></math> = 3.5, B = 30 m.</p>
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<p>The best value found so far for evaluation iterations over 20 trials.</p>
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<p>The optimal configuration of worst-performing Trial 7 among 20 trials.</p>
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<p>Average values of best solutions found by optimization methods.</p>
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<p>The original configuration of the seawall cross-section with composite slopes and a berm.</p>
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<p>The optimal configuration of the seawall cross-section with composite slopes and a berm.</p>
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19 pages, 6182 KiB  
Article
Multi-Point Seawall Settlement Prediction with Limited Data Volume Using an Improved Fractional-Order Grey Model
by Peng Qin, Chunmei Cheng, Zhenzhu Meng, Chunmei Ding, Sen Zheng and Huaizhi Su
Fractal Fract. 2024, 8(7), 423; https://doi.org/10.3390/fractalfract8070423 - 19 Jul 2024
Viewed by 624
Abstract
Settlement prediction based on monitoring data holds significant importance for engineering maintenance of seawalls. In practical engineering, the volume of the collected monitoring data is often limited due to the restrictions of devices and engineering budgets. Previous studies have applied the fractional-order grey [...] Read more.
Settlement prediction based on monitoring data holds significant importance for engineering maintenance of seawalls. In practical engineering, the volume of the collected monitoring data is often limited due to the restrictions of devices and engineering budgets. Previous studies have applied the fractional-order grey model to time series prediction under the situation of limited data volume. However, the performance of the fractional-order grey model is easily affected by the inappropriate settings of fractional order. Also, the model cannot make dynamic predictions due to the characteristic of fixed step size. To solve the above problems, in this paper, the genetic algorithm with enhanced search capabilities was employed to solve the premature convergence problem. Additionally, to solve the problem of the fractional-order grey model associated with fixed step size, the real-time tracing algorithm was introduced to conduct equal-dimensionally recursive calculation. The proposed model was validated using monitoring data of four monitoring points at Haiyan seawall in Zhejiang province, China. The prediction performance of the proposed model was then compared with those of the fractional-order GM(1,1), integer-order GM(1,1), and fractal theory model. Results indicate that the proposed model significantly improves the prediction performance compared to other models. Full article
(This article belongs to the Special Issue Applications of Fractional-Order Grey Models)
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<p>Working principle of genetic algorithm-based optimization.</p>
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<p>Schematic representation of the real-time tracing algorithm.</p>
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<p>Flowchart of the proposed model.</p>
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<p>The (<b>a</b>) geographic location and (<b>b</b>) air-view of the Haiyan seawall.</p>
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<p>The distribution of the soil layers and monitoring points at the Haiyan seawall.</p>
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<p>Time variation in the monitored settlement at monitoring points SS5, SS6, SS7, and SS8.</p>
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<p>Evolution of fractional order <span class="html-italic">r</span> and <span class="html-italic">f</span> (<span class="html-italic">r</span>).</p>
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<p>Time evolution of the predicted and monitored settlement at the selected monitoring points: (<b>a</b>) SS5, (<b>b</b>) SS6, (<b>c</b>) SS7, (<b>d</b>) SS8.</p>
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<p>Time evolution of the relative residual of the predicted and monitored settlement at each monitoring points: (<b>a</b>) SS5, (<b>b</b>) SS6, (<b>c</b>) SS7, (<b>d</b>) SS8.</p>
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<p>Time evolution of fitting and predicting results of seawall settlement at the selected monitoring points using the four selected models: (<b>a</b>) SS5, (<b>b</b>) SS6, (<b>c</b>) SS7, (<b>d</b>) SS8.</p>
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<p>Time evolution of the relative residual of seawall settlement at the selected monitoring points using the four selected models: (<b>a</b>) SS5, (<b>b</b>) SS6, (<b>c</b>) SS7, (<b>d</b>) SS8.</p>
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<p>Comparison of the R<sup>2</sup> of the fitting and testing data at each monitoring point: (<b>a</b>) SS5, (<b>b</b>) SS6, (<b>c</b>) SS7, (<b>d</b>) SS8 using the four selected models.</p>
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<p>Comparison of the MRE of the fitting and testing data at each monitoring point: (<b>a</b>) SS5, (<b>b</b>) SS6, (<b>c</b>) SS7, (<b>d</b>) SS8 using the four selected models.</p>
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30 pages, 39898 KiB  
Article
Inundation Characteristics’ Prediction of Storm Surge under Relative Sea Level Rise Scenarios: A Case Study of Taizhou, Zhejiang Province
by Tangqi Zhao, Xiaomin Li, Suming Zhang, Qi Hou, Xuexue Du and Jie Zhang
J. Mar. Sci. Eng. 2024, 12(6), 1030; https://doi.org/10.3390/jmse12061030 - 20 Jun 2024
Cited by 1 | Viewed by 1021
Abstract
Storm surge is the most serious marine disaster in China, and the inundation characteristics of storm surge are the key indicators of disaster severity. Especially in the context of relative sea level rise (RSLR), it is very important to rapidly and accurately estimate [...] Read more.
Storm surge is the most serious marine disaster in China, and the inundation characteristics of storm surge are the key indicators of disaster severity. Especially in the context of relative sea level rise (RSLR), it is very important to rapidly and accurately estimate the inundation characteristics of storm surge for the risk assessment and emergency management of storm surge disasters. Taking Taizhou city, Zhejiang Province, as the study area, this paper constructed an RSLR scenario library considering absolute sea level rise, land subsidence and storm surge water increase. The scenario library includes 72 scenarios, consisting of a combination of four absolute sea level rise scenarios, three land subsidence scenarios, three timescales (2030, 2050 and 2100) and two storm surge water increase scenarios. Then, an improved passive inundation method was used to predict and analyze the inundation characteristics of storm surge under each scenario. This improved method combines the advantages of the accurate active inundation method and the rapid passive inundation method, and is suitable for rapid and accurate estimation of the storm surge inundation characteristics, which can meet the needs of a storm surge disaster risk assessment and emergency response. The prediction and analysis results show that a minor RSLR can also cause a large-scale inundation in coastal areas of Taizhou. When the value of RSLR exceeds the critical value (0.6 m), it may significantly increase the expansion of the inundation area of storm surge. At a relative sea level rise of 1.57 m (extreme scenario in 2100), the inland storm surge inundation of low-risk areas may become high-risk areas. Finally, the quantitative measures for preventing storm surge disasters were put forward according to the current situation of the coast in Taizhou. Without considering storm surge and superimposed general surge, the existing 20-year return period standard seawall can effectively protect against storm surge under various scenarios. In the case of maximum water increase, it is expected that effective protection will remain until 2030, but the standard of the seawall defense will need to be improved in 2050 and 2100. Full article
(This article belongs to the Special Issue Sea Level Rise and Related Hazards Assessment)
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<p>Study area. (<b>a</b>) Location and topography of Taizhou, (<b>b</b>) contour near inundation areas.</p>
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<p>The implementation flow of the improved passive inundation method.</p>
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<p>The inundation range extracted from Sentinel-1B images (<b>a</b>) and the inundation range estimated by the proposed method (<b>b</b>).</p>
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<p>Sea level change in Zhejiang Province from 2007 to 2020.</p>
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<p>Water increase of storm surge in Taizhou from 2011 to 2021 (unit: m): (<b>a</b>) raw data, (<b>b</b>) extreme values removed.</p>
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<p>The estimated inundation area of storm surge under each scenario in Taizhou (SS<sub>E</sub>: relative sea level rise superimposed general water increase of storm surge; SS<sub>M</sub>: relative sea level rise superimposed maximum water increase of storm surge).</p>
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<p>Impacts of extreme RSLR on coastal areas of Taizhou in 2030, 2050 and 2100.</p>
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<p>Inundation area under RSLR superimposed with the general storm surge in 2030 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Inundation area under RSLR superimposed with the general storm surge in 2050 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Inundation area under RSLR superimposed with the general storm surge in 2100 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Inundation area under RSLR superimposed with the maximum storm surge in 2030 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Inundation area under RSLR superimposed with the maximum storm surge in 2050 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Inundation area under RSLR superimposed with the maximum storm surge in 2100 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Coast type distribution map of Taizhou.</p>
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<p>The designed seawalls under extreme RSLR scenarios in 2030, 2050 and 2100.</p>
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<p>Seawalls in 2030 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Seawalls in 2050 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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<p>Seawalls in 2100 (there are 12 scenarios in total, SSP1-2.6-Low and SSP5-8.5-High are selected here, and the other scenarios are shown in the <a href="#app1-jmse-12-01030" class="html-app">Supplementary Materials</a>).</p>
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23 pages, 3765 KiB  
Article
Settlement Forecast of Marine Soft Soil Ground Improved with Prefabricated Vertical Drain-Assisted Staged Riprap Filling
by Xue-Ting Wu, Jun-Ning Liu, Adel Alowaisy, Noriyuki Yasufuku, Ryohei Ishikura and Meilani Adriyati
Buildings 2024, 14(5), 1316; https://doi.org/10.3390/buildings14051316 - 7 May 2024
Viewed by 821
Abstract
By comparing different settlement forecast methods, eight methods were selected considering the creep of marine soft soils in this case study, including the Hyperbolic Method (HM), Exponential Curve Method (ECM), Pearl Growth Curve Modeling (PGCM), Gompertz Growth Curve Modeling (GGCM), Grey (1, 1) [...] Read more.
By comparing different settlement forecast methods, eight methods were selected considering the creep of marine soft soils in this case study, including the Hyperbolic Method (HM), Exponential Curve Method (ECM), Pearl Growth Curve Modeling (PGCM), Gompertz Growth Curve Modeling (GGCM), Grey (1, 1) Model (GM), Grey Verhulst Model (GVM), Back Propagation of Artificial Neural Network (BPANN) with Levenberg–Marquardt Algorithm (BPLM), and BPANN with Gradient Descent of Momentum and Adaptive Learning Rate (BPGD). Taking Lingni Seawall soil ground improved with prefabricated vertical drain-assisted staged riprap filling as an example, forecasts of the short-term, medium-term, long-term, and final settlements at different locations of the soft ground were performed with the eight selected methods. The forecasting values were compared with each other and with the monitored data. When relative errors were between 0 and −1%, both the forecasting accuracy and engineering safety were appropriate and reliable. It was concluded that the appropriate forecast methods were different not only due to the time periods during the settlement process, but also the locations of soft ground. Among these methods, only BPGD was appropriate for all the time periods and locations, such as at the edge of the berm, and at the center of the berm and embankment. Full article
(This article belongs to the Section Building Structures)
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<p>Forecast methods used in this study.</p>
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<p>Geographic position of Lingni Seawall (Google Maps).</p>
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<p>Typical foundation treatment and settlement monitoring cross-section of Lingni Seawall.</p>
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<p>Staged riprap loading and monitored settlement data at Points A, B, and C. (Notes: 550 d—The full loading time at the center of the embankment, after which the loading will keep constant for the rest period; 665 d—The time of boundary point for settlement fitting and forecasting).</p>
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<p>Three-layer perceptron network of BPANN.</p>
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<p>BPANN at Point B: (<b>a</b>) neural network of BPLM and BPGD; (<b>b</b>) weight matrices of BPLM; (<b>c</b>) weight matrices of BPGD.</p>
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<p>Monitored data and settlement fitting and forecasting results of Point A.</p>
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<p>Monitored data and settlement fitting and forecasting results of Point B.</p>
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<p>Monitored data and settlement fitting and forecasting results of Point C.</p>
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<p>Comparison of relative errors of different forecast methods: (<b>a</b>) error analysis of Point A, (<b>b</b>) error analysis of Point B, (<b>c</b>) error analysis of Point C.</p>
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<p>Comparison of final settlement forecasts: (<b>a</b>) forecasts at Point A, (<b>b</b>) forecasts at Point B, (<b>c</b>) forecasts at Point C, (<b>d</b>) forecasted final settlement values.</p>
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13 pages, 3287 KiB  
Article
Comparing the Structure of Fish Assemblage among Natural and Artificial Shallow Rocky Habitats
by Laura García-Salines and Pablo Sanchez-Jerez
Oceans 2024, 5(2), 244-256; https://doi.org/10.3390/oceans5020015 - 6 May 2024
Viewed by 1441
Abstract
Artificial coastal structures, such as seawalls, breakwaters, and groins, can exert various impacts on the fish communities in the nearby regions. This study focuses on assessing the ecological effects of coastal infrastructure on marine environments, by comparing, at different seasons, the habitat complexity [...] Read more.
Artificial coastal structures, such as seawalls, breakwaters, and groins, can exert various impacts on the fish communities in the nearby regions. This study focuses on assessing the ecological effects of coastal infrastructure on marine environments, by comparing, at different seasons, the habitat complexity and heterogeneity, as well as their effects on fish assemblages, between the artificial habitat created with the intention of constructing a marina (Puerto Amor) and the natural habitats surrounding the Cabo de la Huerta area in Alicante (Spain). Employing an asymmetric design and examining two temporal and spatial scales, we utilized visual censuses in snorkeling to gauge the abundance and size of fish species, alongside various parameters related to habitat complexity and heterogeneity. The overarching hypothesis is that fish populations associated with artificial habitats will differ in terms of abundance, biomass, species richness, and diversity compared to fish populations associated with natural habitats, due to changes in complexity and heterogeneity. The findings indicate a shift in fish assemblages; for example, the family Labridae showed differences between the two habitat types for several species. These changes were due to the influences of the Posidonia oceanica meadow and algae like Jania rubens; being influenced by biological variables such as Ellisolandia elongata, Oculina patagonica, and Sarcotragus spinosulus; as well as physical variables such as stones, gravel, and blocks. While there is evidence of alteration in fish assemblages due to changes in habitat structure, there is also an increase in richness (9 species/m2) and total abundance and biomass (1000 ind./m2 and 1700 g/m2, respectively) in the artificial habitat. Multivariate analyses reveal that the fish community in Puerto Amor is less homogeneous than the one in the natural habitat. However, these analyses also indicate an overlap between the communities of both habitats, suggesting substantial similarity despite the noted differences. Consequently, although the habitat alteration has impacted fish populations, it has not diminished abundance, biomass, or species richness. In conclusion, the artificial rocky habitat resulting from the construction attempt at Puerto Amor harbor has fish populations with ecological significance and its removal could lead to undesirable impacts in the area, as the fish assemblages have become well established. Full article
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<p>Impact location; evolution of the Puerto Amor project (ETRS89/UTM 30S 724,103.16 m E, 4,248,566.12 m N). (<b>a</b>) 1977 (Interministerial Flight, National Geographic Institute image, <a href="http://www.ign.es" target="_blank">www.ign.es</a>; accessed on 20 March 2022), (<b>b</b>) 1985 (National Flight, National Geographic Institute image, <a href="http://www.ign.es" target="_blank">www.ign.es</a>; accessed on 20 March 2022), (<b>c</b>) 1989 (Coastal Flight National Geographic Institute image, <a href="http://www.ign.es" target="_blank">www.ign.es</a>; accessed on 20 March 2022), (<b>d</b>) 1999 (Quinquennial Flight, National Geographic Institute image, <a href="http://www.ign.es" target="_blank">www.ign.es</a>; accessed on 20 March 2022), (<b>e</b>) 2002 (Photogrammetric Flight with scanned color, Valencian Cartographic Institute image, icv.gva.es; accessed on 20 March 2022), and (<b>f</b>) present (Google Earth Pro image; accessed on 20 March 2022).</p>
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<p>Study locations in the coastal environment of Cabo de la Huerta (modified in QGIS).</p>
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<p>(<b>a</b>) Boxplot of total abundance of fishes (individual/m<sup>2</sup>), (<b>b</b>) total biomass of fishes (g/m<sup>2</sup>), (<b>c</b>) species richness (number of species/m<sup>2</sup>), and (<b>d</b>) Shannon diversity index (bit ind<sup>−1</sup>), depending on the type of rocky habitat. Variance appears with error bars, with the mean in red, the median in black and bold, the boxes of interquartile ranges in grey, and the outliers represented with circles.</p>
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<p>Abundance of the Sparidae family species (mean ± standard error), depending on the locations and the seasons.</p>
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<p>Abundance of the Labridae family species (mean ± standard error), depending on the locations and the seasons.</p>
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<p>Abundance of the Serranidae family species (mean ± standard error), depending on the locations and the seasons.</p>
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<p>Redundancy analysis (RDA) of the biological features of the rocky habitat (<b>left</b>) and of the physical features of the rocky habitat (<b>right</b>).</p>
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18 pages, 8110 KiB  
Article
Data-Driven Assessment of the Impact of Hurricanes Ian and Nicole: Natural and Armored Dunes in the Aftermath of Hurricanes on Florida’s Central East Coast
by Kelly M. San Antonio, Daniel Burow, Hyun Jung Cho, Matthew J. McCarthy, Stephen C. Medeiros, Yao Zhou and Hannah V. Herrero
Remote Sens. 2024, 16(9), 1557; https://doi.org/10.3390/rs16091557 - 27 Apr 2024
Cited by 2 | Viewed by 2294
Abstract
Hurricanes Ian and Nicole caused devastating destruction across Florida in September and November 2022, leaving widespread damage in their wakes. This study focuses on the assessment of barrier islands’ shorelines, encompassing natural sand dunes and dune vegetation as well as armored dunes with [...] Read more.
Hurricanes Ian and Nicole caused devastating destruction across Florida in September and November 2022, leaving widespread damage in their wakes. This study focuses on the assessment of barrier islands’ shorelines, encompassing natural sand dunes and dune vegetation as well as armored dunes with man-made infrastructure such as seawalls. High-resolution satellite imagery from Planet was used to assess the impacts of these hurricanes on the beach shorelines of Volusia, Flagler, and St. Johns Counties on the Florida Central East Coast. Shorefront vegetation was classified into two classes. Normalized Difference Vegetation Index (NDVI) values were calculated before the hurricanes, one month after Hurricane Ian, one month after Hurricane Nicole, and one-year post landfall. LiDAR (Light Detection and Ranging) was incorporated to calculate vertical changes in the shorelines before and after the hurricanes. The results suggest that natural sand dunes were more resilient as they experienced less impact to vegetation and elevation and more substantial recovery than armored dunes. Moreover, the close timeframe of the storm events suggests a compound effect on the weakened dune systems. This study highlights the importance of understanding natural dune resilience to facilitate future adaptive management efforts because armored dunes may have long-term detrimental effects on hurricane-prone barrier islands. Full article
(This article belongs to the Special Issue Remote Sensing and Ecosystem Modeling for Nature-Based Solutions)
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<p>Map of the study area along the Florida East Central Coast with paths from Hurricanes Ian and Nicole. The inset map displays the extent of the region of interest (ROI) used in this study, a narrow and long stretch of the oceanfront coastlines between Ponce Inlet Beach from Ponce Inlet in Volusia County and St. Augustine Inlet in St. Johns County (inlets designated by yellow stars).</p>
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<p>Photos of some of the severe instances of dune erosion and property destruction in the study area. The photos were taken shortly after Hurricane Nicole on 11 November 2022, in the Wilbur-by-the-Sea area (near Ponce Inlet) at approximately 29.126N, 80.954W (courtesy of Daniel Burow).</p>
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<p>Pre (<b>top</b>) and Post (<b>bottom</b>) lidar digital elevation models for select locations in the region of interest. (<b>A</b>,<b>D</b>) St. Augustine Inlet (undeveloped); (<b>B</b>,<b>E</b>) Ocean Hammock Golf Course (developed with open space); and (<b>C</b>,<b>F</b>) south of Daytona Beach Main Street Pier (high-intensity development).</p>
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<p>Example of a natural dune with three categories (secondary vegetation, edge of primary vegetation, and sand in front of natural foredune). The photo was taken on 26 February 2024, on Ponce Inlet Beach (courtesy of Kelly San Antonio).</p>
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<p>Example of an armored dune with three categories (secondary vegetation, edge of primary vegetation, and sand in front of armored foredune). The photo was taken on 26 February 2024, near Toronita Avenue Beach Park (courtesy of Kelly San Antonio).</p>
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<p>Workflow diagram of data and methods.</p>
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<p>NDVI trends for each of the six clusters. The timing of the hurricanes is indicated by the vertical dashed lines.</p>
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<p>Cluster classifications of pixels in three regions of interest in the study area: Wilbur Beach (<b>top</b>), Ponce Inlet (<b>middle</b>), and the Washington Oaks State Park region near Palm Coast (<b>bottom</b>). Background Planet imagery obtained in December 2021.</p>
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<p>Mean NDVI from selected points of secondary vegetation (vegetation), edge of primary vegetation (edge), and sand, comparing natural vs. armored dunes. Eighty sample points were selected for each of the categories.</p>
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<p>Mean elevation (m) from selected points of secondary vegetation (vegetation), edge of primary vegetation (edge), and sand, comparing natural vs. armored dunes. Eighty sample points were selected for each of the categories.</p>
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