Hydrodynamic Model Research Articles

Coupled kinetic and hydrodynamic model for a carbonator reactor of calcium looping process: Sulfur dioxide effect

The application of the calcium looping (CaL) process for CO2 capture has gained recognition as a highly efficient technology in mitigating greenhouse gases emission. In this study, by considering the characteristics of the adsorbent and the hydrodynamics of the fluidized bed in the fast fluidization regime, a fractal-like random pore kinetic model and a 1D hydrodynamic model were combined together. In order to validate the kinetic model, experimental carbonation data obtained from a lab-scale fluidized bed reactor under realistic operational condition and in the absence/presence of SO2 gas were used. The results demonstrated a satisfactory agreement between the model and experimental data, as indicated by the maximum absolute error of 1.23% and 1.78% in the absence and presence of SO2, respectively. Based on sensitivity analysis, the efficiency of the carbonator reactor was found to be predominantly affected by the solid inventory in the bed and the gas inlet velocity. Also, the results of this analysis indicate that in the presence of SO2, a higher make-up flow rate leads to a more pronounced enhancement in the efficiency of the carbonator reactor, as compared to the absence of SO2 in the reaction environment. Results of modelling indicated that the presence of SO2 necessitated a 36.5-fold increase in the minimum-required make-up flow to attain comparable efficiency obtained in the condition of the absence of SO2. Furthermore, the results of modelling as a function of number of cycles demonstrated a substantial decline in the efficiency of the carbonator reactor, which in the absence of SO2, the efficiency decreased from 68.13% to 18.81%, while in the presence of SO2, it decreased from 45.53% to 4.75% over 100 sequential cycles.

Investigation on the modeling and simulation of hydrodynamics in asymmetric conduction laser micro-welding of austenitic stainless steel and its process optimization

Laser micro-welding is a joining technology utilized across various high-value industries, like medical, automotive, e-mobility, and aerospace. A trial-and-error process to identify welding parameters does not necessarily lead to optimized quality levels. Furthermore, offline non-destructive examination methods often launched to verify welding quality may inadvertently trigger excessive costs and time delays, ultimately failing to guarantee defect-free welds. In response to these challenges, this article introduces an advanced multiscale model designed to unravel the intricate dynamics of hydrodynamics and the overarching physics within laser micro-welding melting pools. Developed using the COMSOL software package, the model adeptly demonstrates how surface tension gradients shape the geometry of welds, thus influencing their quality. This knowledge allows the mapping of welding defects. One of the novelties of the article is to introduce geometric dissimilar welding conditions by simulating an asymmetric edge joint. It shows a study on a new, unstudied way to laser weld with many applications in the field. The model further establishes its utility in design experiments to determine parameter, tolerance, and system design. Moreover, the insights garnered from understanding and controlling these drivers have far-reaching implications for the advancement of subsequent methodological research and the development of in-situ quality control practices by characterizing the welding defects. Finally, the results shows that the discouragingly high computational costs restrict its potential application to support a Digital Twin.

A deep-learning model for rapid spatiotemporal prediction of coastal water levels

With the increasing impact of climate change and relative sea level rise, low-lying coastal communities face growing risks from recurrent nuisance flooding and storm tides. Thus, timely and reliable predictions of coastal water levels are critical to resilience in vulnerable coastal areas. Over the past decade, there has been increasing interest in utilizing machine learning (ML) based models for emulation and prediction of coastal water levels. However, flood advisory systems still rely on running computationally demanding hydrodynamic models. To alleviate the computational burden, these physics-based models are either run at small scales with high resolution or at large scales with low resolution. While ML-based models are very fast, they face challenges in terms of ensuring reliability and ability to capture any surge levels. In this paper, we develop a deep neural network for spatiotemporal prediction of water levels in coastal areas of the Chesapeake Bay in the U.S. Our model relies on data from numerical weather prediction models as the atmospheric input and astronomical tide levels, while its outputs are time series of predicted water levels at several tide gauge locations across the Chesapeake Bay. We utilized a CNN-LSTM setting as the architecture of the model. The CNN part extracts the features from a sequence of gridded wind fields and fuses its output to several independent LSTM units. The LSTM units concatenate the atmospheric features with respective astronomical tide levels and produce water level time series. The novel contribution of the present work is in spatiotemporality and in prioritization of the physical relationships in the model to maintain a high analogy to hydrodynamic modeling, either in the network architecture or in the selection of predictors and predictands. The results show that this setting yields a strong performance in predicting coastal water levels that cause flooding from minor to major levels. We also show that the model stands up successfully to the rigorous comparison with a high-fidelity ADCIRC model, yielding mean RMSE and correlation coefficient of 14.3 cm and 0.94, respectively, in two extreme cases, versus 12.30 cm and 0.96 for the ADCIRC model. The results highlight the practical feasibility of employing fast yet inexpensive data-driven models for resilient coastal management.

Effects of sea level rise and tidal flat growth on tidal dynamics and geometry of the Elbe estuary

Abstract. Future global mean sea level rise (SLR) will affect coastlines and estuaries in the North Sea and therefore also coastal protection structures, unique local ecosystems and important waterways. SLR will not only raise water levels but also influence tidal dynamics and morphodynamics, which is why the tidal flats of the Wadden Sea can grow to a certain extent with SLR. Investigations on the effects of climate-change-induced SLR and the related potential bathymetric changes inside of estuaries form an important basis for identifying vulnerabilities and developing appropriate adaptation strategies. To analyse the influence of potential SLR and tidal flat elevation scenarios on the tidal dynamics in the Elbe estuary, we used a highly resolved hydrodynamic numerical model of the German Bight. The analysis results show increasing tidal range in the Elbe estuary solely due to SLR. They also reveal strongly varying changes with different tidal flat growth scenarios: while tidal flat elevation up to the mouth of the estuary can cause tidal range to decrease relative to SLR alone, tidal flat elevation in the entire estuary can lead to an increase in tidal range relative to SLR alone. Further analyses show how the geometric parameters of the Elbe estuary are changing due to SLR and tidal flat elevation. We discuss how these changes in estuarine geometry can provide an explanation for the changes in tidal range.

Wind-driven hydrodynamic characteristics of Lake Taihu, a large shallow lake in China.

As an essential drinking water source and one of the largest eutrophic shallow lakes in China, the management of Lake Taihu requires an adequate understanding of its hydrodynamic characteristics. Studying the hydrodynamic characteristics of Lake Taihu based on field observations is limited owing to its large area and the lack of flow field stability. Previous studies using hydrodynamic models experienced challenges, such as dimensionality and lack of dynamic response analysis between flow field and realistic wind; therefore, the results were still inconclusive. In this study, a 3D model of Lake Taihu, calibrated and validated based on field observations, was used to simulate and compare three scenarios: windless, steady wind, and realistic wind. The hydrodynamic characteristics of Lake Taihu were analyzed as close to the actual conditions as possible. The results showed that wind-driven currents dominated the flow field in Lake Taihu, and the horizontal velocity driven by wind was more than 6 times that without wind. Observing a stable flow field in Lake Taihu was difficult because of the variability of realistic wind. The hydrodynamic characteristics of Lake Taihu were defined as "strongly affected by wind," "higher on the surface and smaller at the bottom," and "difference between the surface and the bottom." Vertical turbulent kinetic energy can be used to characterize the variable flow field of a wind-driven lake and has a positive correlation with wind speed. Therefore, it could be used as a key component to predict water blooms with practical implications.

Enhancing Digital Elevation Model Accuracy for Flood Modelling – A Case Study of the Ciberes River in Cirebon Indonesia

Topographic conditions represented by the Digital Elevation Model (DEM) are essential in flood inundation models. The DEM which is categorised as a Digital Surface Model (DSM) stores the height information, be-sides the ground and non-ground elevation required for preprocessing before being employed in hydrologic applications, particularly in relation to flood modelling by removing non-ground elevation along the flood plain and river channels. The improvement in the accuracy of flood inundation modelling is crucial in reduc-ing the impact of flood disasters. This study aims to compare the accuracy level of the DEM based on Ter-raSAR-X data with the filtering process using slope-based filtering and combining the cross-sectional river profile from the field measurement to the filtered DEM. The result confirms that the accuracy of the DEM product is improved via filtering to remove non-ground elevations and a significant improvement in accuracy by means of fused river profile information to filtered DEM. The results of adding river information to the DEM could provide a representation closer to the cross-sectional profile of the river based on field measure-ments within the accuracy level Mean Absolute Error 2.51 m, 2.72 m and 1.91 m in the left overbank, right overbank and centre of the river, respectively. The performance results of the 2-dimensional flood hydrody-namic modelling using HEC-RAS derived from the DEM before filtering, after filtering, and the addition of river information show increasing accuracy in flood depth at each stage of the DEM processing. There is an improvement in accuracy in flood depth of approximately 11.67% using the filtered DEM, besides an in-crease in accuracy in flood depth by 24.98% utilising the filtered DEM with added river channel information.

Precore mutation enhances viral replication to facilitate persistent infection especially in HBeAg-negative patients

Naturally occurred precore (PC, G1896A) and/or basal core promoter (BCP, A1762T/G1764A) mutations are prevalent in chronic HBV-infected patients, especially those under HBeAg-negative status. However, the replicative capacity of HBV with PC/BCP mutations remains ambiguous. Herein, meta-analysis showed that, only under HBeAg-negative status, the serum HBV DNA load in patients with PC mutation was 7.41-fold higher than those without the mutation. Both PC mutation alone and BCP ​+ ​PC mutations promoted HBV replication in cell and hydrodynamic injection mouse models. In human hepatocyte chimeric mouse model, BCP ​+ ​PC mutations led to elevated replicative capacity and intrahepatic core protein accumulation. Mechanistically, preC RNA harboring PC mutation could serve as mRNA to express core and P proteins, and such pgRNA-like function favored the maintenance of cccDNA pool under HBeAg-negative status. Additionally, BCP ​+ ​PC mutations induced more extensive and severe human hepatocyte damage as well as activated endoplasmic reticulum stress and TNF signaling pathway in livers of chimeric mice. This study indicates that HBeAg-negative patients should be monitored on HBV mutations regularly and are expected to receive early antiviral treatment to prevent disease progression.

Lessons from the calibration and sensitivity analysis of a fish larval transport model

Numerous fish populations show strong year-to-year variations in recruitment. The early life stages play a crucial role in determining recruitment and dispersal patterns. A helpful tool to understand recruitment and dispersal involves simulations with a Lagrangian transport model, which results from the coupling between a hydrodynamic model and an individual-based model. Larval transport models require sound knowledge of the biological processes governing larval dispersal, and they may be highly sensitive to the parameters selected. Various assumptions about larval traits, behaviour and other model parameters can be tested by comparing simulation results with field data to identify the most sensitive parameters and to improve model calibration. This study shows that biological parameterization is more important than inter-annual variability in explaining the year-to-year differences in larval recruitment of common sole in the North Sea and the eastern English Channel. In contrast, year-to-year variability of connectivity leads to higher variability than changes in the biological parameters. The most influential parameters are pelagic larval duration, spawning period and mortality. Calibration over a 12 yr recruitment survey shows that a scenario with low mortality associated with a long larval duration and behaviour involving nycthemeral and tidal migration best reproduces the observations. This research provides insights into factors influencing fish dispersal and recruitment, suggesting a strategy for enhancing the accuracy of models in upcoming studies. The study supports the improvement of larval dispersal modelling by incorporating an easily applicable sensitivity analysis for both calibration and validation. Incorporating sensitivity analyses enhances larval dispersal models, providing performing tools that can contribute to informed fisheries management and understanding of recruitment variability.

Impacts of extreme river discharge on coastal dynamics and environment: Insights from high-resolution modeling in the German Bight

The intricate relationship between extreme river discharge and its consequential effects on coastal basins’ environment and dynamics remains a subject of profound significance. The impact of extreme river discharge on coastal basin dynamics and environment is a complex phenomenon, particularly relevant in the context of the German Bight. The inflow of freshwater from rivers into the German Bight plays a crucial role in driving the complex thermohaline circulation. Addressing the challenges posed by local hydro-meteorological extremes, compounded by strong wind waves, currents and tides is vital for comprehensive impact assessment. Utilizing the Geesthacht Coupled cOAstal model SysTem (GCOAST) with high-resolution configuration, we investigate the sensitivity of the thermohaline properties to the river forcings. By incorporating river discharge as lateral land forcing in a coupled hydrodynamic and wave model, we conducted five sensitivity experiments. Our findings reveal that the simulated temperatures closely match measurements in all experiments. The salinity, however, is remarkably sensitive to the variation of freshwater from the rivers Elbe and Ems in the German Bight, causing the haline stratification. The statistical evaluation, as demonstrated by the Taylor diagram at the Marnet DB station, underscores the skill of the Mesoscale Hydrologic Model (mHM) in generating the freshwater discharge that drives the thermohaline characteristics of the German Bight, especially during events like the June 2013 flooding. Significantly, the use of climatological runoff proves to be ineffective in simulating stratification during extreme flooding events. In essence, this investigation enhances our understanding of the pivotal role played by high-frequency river freshwater buoyancy. It emerges as a driving force behind salinity fluctuations during extreme floods, providing valuable insights into coastal dynamics within the German Bight.

Impact of reclamation projects on water quality in jinmeng bay, China

Since 2015, green tides have recurred annually in Jinmeng Bay (JMB), China. Reclamation projects have been considered an important anthropogenic perturbation in JMB for green tides. A coupled hydrodynamic and water quality model was used to simulate hydrodynamic and transport processes for different artificial structure scenarios. Numerical results prove that reclamation projects exert a significant impact on the water environment in JMB, and nutrient distributions are mainly influenced by Conch Island, which decreases pollutant dilution and diffusion in coastal waters. Moreover, the average residence time increases by about 35% after the construction of the two artificial islands. Areas with long residence time coincide with the major sources of the green tide blooms, which declares that the weak water exchange capacity affected by artificial islands is responsible for the water quality degradation. The increased nutrient levels and hydraulic residence time also suggest the high possibility of green algal blooms in JMB.

Improving our understanding of future tropical cyclone intensities in the Caribbean using a high-resolution regional climate model

The Caribbean region is prone to the strong winds and low air pressures of tropical cyclones and their corresponding storm surge that driving coastal flooding. To protect coastal communities from the impacts of tropical cyclones, it is important to understand how this impact of tropical cyclones might change towards the future. This study applies the storyline approach to show what tropical cyclones Maria (2017) and Dorian (2019) could look like in a 2 °C and 3.4 °C warmer future climate. These two possible future climates are simulated with a high-resolution regional climate model using the pseudo global warming approach. Using the climate response from these simulations we apply a Delta-quantile mapping technique to derive future changes in wind speed and mean sea level pressure. We apply this Delta technique to tropical cyclones Maria and Dorian’s observed wind and pressure fields to force a hydrodynamic model for simulating storm surge levels under historical and future climate conditions. Results show that the maximum storm surge heights of Maria and Dorian could increase by up to 0.31 m and 0.56 m, respectively. These results clearly show that future changes in storm surge heights are not negligible compared to end-of-the-century sea level rise projections, something that is sometimes overlooked in large-scale assessments of future coastal flood risk.

A complete methodology to assess hydraulic risk in small ungauged catchments based on HEC-RAS 2D Rain-On-Grid simulations

This paper explores the use of the rain-on-grid (or direct rainfall) method for flood risk assessment at a basin scale. The method is particularly useful for rural catchments with small vertical variations and complex interactions with man-made obstacles and structures, which may be oversimplified by traditional hydrologically based estimations. The use of a hydrodynamic model solving mass and momentum conservation equations allows the simulation of runoff over the watershed at a basin scale. As a drawback, more detailed and spatially distributed data are needed, and the computational time is extended. On the other hand, a smaller number of parameters is needed compared to a hydrological model. Roughness and rainfall loss coefficients need to be calibrated only. The direct rainfall methodology was here implemented within the two-dimensional HEC-RAS model for the low-land rural, and ungauged, watershed of the Terdoppio River, Northern Italy. The resulting hydrographs at the closing section of the watershed were compared to synthetic design hydrographs evaluated through pure hydrological modelling, showing agreement on the peak discharge values for the low-probability scenarios, but not on the total volumes. The results in terms of water depth and flow velocity maps were used to create flood hazard maps using the Australian Institute for Disaster Resilience methodology. The Index of Proportional Risk model was then adopted to generate a basin-scale flood risk map, by combining flood hazard maps, damage functions for different building-use classes, and the value of reconstruction and content per unit area.

Theoretical Hydrodynamic Modeling of the Fluidized Bed Photoreactor (FBP) Using Computational Fluid Dynamics (CFD): Fluidization Conditions for TiO2-CuO Immobilized on Beach Sand Granules

The flow regime is essential in the photoreactor’s performance in pollutant degradation in the aqueous medium, especially in fluidized systems. Therefore, this study is focused on determining the fluidization conditions of a granular catalyst based on TiO2-CuO nanoparticles (1 wt.% CuO) immobilized on beach sand granules using an FBP photoreactor. COMSOL Multiphysics 6.0 was employed for inlet velocities between 0.1 m/s and 1.0 m/s, mainly from the Reynolds averaged Navier–Stokes (RANS) turbulence model and the Stokes drag law. The results indicated that the average velocities in the annular section are much higher (4.11ut and 5.42ut) than the required particle terminal velocity. Moreover, the pressure contour lines revealed that these flow velocities do not represent excessive pressures in the concentric cylinders, with maximum gauge pressures of 740.52 Pa and 1310 Pa for inlet velocities Uo=0.75 and 1.0 m/s, respectively. Finally, it was determined that the Reynolds number adjusted (Repf) values lower than or equal to 1.37×10−3 allow high fluidization after 2 seconds. This information makes it possible to adapt and assemble the FBP equipment for future photocatalytic evaluation.

Flood Modeling in a Composite System Consisting of River Channels, Flood Storage Areas, Floodplain Areas, Polder Areas, and Flood-Control-Protected Areas

The Linhuaigang flood control project (LFCP), situated on the Huaihe River, China, uses the river channels upstream of the LFCP, together with the hinterland areas outside the channels, to retain and store fluvial floodwaters that exceed the downstream channel’s discharge capacity. The hinterland areas are split into seven flood storage areas, three floodplain areas, eight polder areas, and three flood-control-protected areas, and they are connected to the river in various ways. A coupled hydrodynamic model was established to simulate the hydrodynamic and water volume exchange between the river channels and the hinterland areas. The flood storage area, under the control of a flood diversion sluice, was simulated with a 2D hydrodynamic model, and the inflow process initiated by the flood diversion sluice was simulated as a control structure. The polder area was generalized as a reservoir that would be filled in several hours once put into use because of its small size. The uncontrolled inflow process between the flood-control-protected areas and the channel was simulated by means of a dam break model, which could simulate levee breaching. The flooding within the flood-control-protected area, which represents a vast space, was simulated with a 2D hydrodynamic model. The floodplain area was laterally connected to the river channel along the river levee. The difference between the simulated and the measured flood peak water stage did not exceed 0.2 m in 2003 and 2007, indicating that the accuracy of the model was relatively high. In the scenario of a design flood with a return period of 100 years, the flood storage areas and the LFCP were used in the following order: Mengwa, Qiujiahu, Nanrunduan, Shouxihu, Jiangtanghu, Chengxihu, Chengdonghu, and the LFCP. When the Huaihe River encounters a flood with a return period of 1000 years that exceeds the design standard, the highest water stage upstream of the LFCP and Zhengyangguan shall not exceed 29.30 m and 27.96 m after the use of all the flood storage areas, floodplain areas, and flood-control-protected areas. The results of this research can provide technical support for the flood risk management of the LFCP.

Novel approach to the derivation of dam breach parameters in 2D hydrodynamic modeling of earthquake induced dam failures

Current methods of dam breach analyses adopt a deterministic approach. Applying these methods to Concrete Faced Rockfill Dams (CFRD) is fraught with huge levels of uncertainty, especially in the context of natural hazards. The frequency and magnitude of rainfall and earthquakes are higher in today's world. In the literature, the complete collapse of dams is modelled on dam breach parameters that define the dam break outflow but are not related to the return periods of natural hazards. As more new dams are constructed to control the floods in intra-plate seismic regions, this study presents a novel approach to the derivation of generalized dam break parameters for CFRD based on the structural analysis of Finite Element Model (FEM) simulations for peak ground accelerations corresponding to 475 and 2475 year return periods. Furthermore, the occurrence of rainfall and earthquake for different return periods are modelled using 2D hydrodynamic simulations. Results show the significance of generalized dam breach parameters for planning and managing CFRDs during earthquakes. The study emphasizes the utilization of structural analysis outputs for the hydraulic modeling of dam breaks, which will result in more specific and accurate dam break parameters. Additionally, the study has shown that the flood risk and the severity will increase with the intensity of earthquake and rainfall magnitudes. Disaster mitigation strategies can be optimized by considering the integrated occurrence of rainfall and earthquakes based on the probability of occurrence, demonstrated using a case-study dam. Another significant outcome of the study is the effect of soil saturation condition during a dam break, which reveals that areas within 40 km of the dam breach location might be worst affected.

Dynamics of currents in the Qiongzhou strait during spring and summer based on a numerical simulation

A high-precision three-dimensional hydrodynamic model based on the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) was constructed to investigate the characteristics of residual currents in the Qiongzhou Strait during spring and summer. Results reveal an overall westward transport in the strait during spring and summer. However, the results also support the potential occurrence of transient eastward Eulerian residual currents, which should be evident predominantly at the surface in the central and eastern sections of the strait and mainly characterised by subtidal oscillations. The direction and intensity of these residual currents indicate a pronounced influence of pressure gradient forces on both sides of the strait. The eastward flow observed in spring may represent a compensatory mechanism resulting from the relaxation period of long-term easterly winds, whereas the generation of eastward residual currents in summer is influenced by wind stress curl differences in both the western and eastern areas of the strait. The direct impact of the summer monsoon on the flow field in the strait is relatively weak. Additionally, the direction and intensity of the residual currents in the strait exhibit potential interannual variations that are directly associated with interannual wind variations. This study provides valuable insights in relation to the ongoing discourse on the dynamics of residual currents in the Qiongzhou Strait.

Minimal Quantization Model in Pilot-Wave Hydrodynamics.

Investigating how classical systems may manifest dynamics analogous to those of quantum systems is a broad subject of fundamental interest. Walking droplets, which self-propel through a resonant interaction with their own wave field, provide a unique macroscopic realization of wave-particle duality that exhibits behaviors previously thought exclusive to quantum particles. Despite significant efforts, elucidating the precise origin and form of the wave-mediated forces responsible for the walker's quantumlike behavior remained elusive. Here, we demonstrate that, owing to wave interference, the force responsible for orbital quantization originates from waves excited near stationary points on the walker's past trajectory. Moreover, we derive a minimal model with the essential ingredients to capture quantized orbital dynamics, including quasiperiodic and chaotic orbits. Notably, this minimal model provides an explicit distinction between local forces, which account for the walker's preferred speed and wave-induced added mass, and spatiotemporal nonlocal forces responsible for quantization. The quantization mechanism revealed here is generic, and will thus play a role in other hydrodynamic quantum analogs.

Study of the hydrologic and hydrodynamic coupling model (HHDCM) and application in urban extreme flood systems

Based on urban flood hydrology processes and hydrodynamic principles, the stormwater management model (SWMM) was improved upon. The coupling and implementation methods of the SWMM and two-dimensional hydrodynamic model are proposed. The improved SWMM was coupled with the hydrodynamic model both from the vertical and horizontal directions. The hydrology and hydrodynamic coupling model (HHDCM) was constructed and verified by using extreme rainstorm data. Taking July.20 extreme rainstorms (from July 17 to July 20, 2021, i.e., July.20 extreme rainstorm) in Zhengzhou city, Henan Province, China, as an example and using the HHDCM model, the flood disaster caused by July.20 extreme rainstorm was simulated. Based on the simulation results, an inundation distribution map was drawn for the urban area. A comparison between the simulated and measured results reveals that the maximum relative error in the simulated results is 12.5%. Therefore, the HHDCM model proposed in this paper has desirable accuracy and reliability for simulating extreme urban rainstorms and flood disasters.

The significance of radiative heat and mass transfer through a vertical sheet with chemical reaction: Designing by artificial approach Levenberg-Marquardt

The present study examines the impact of incorporating soft computing algorithms during neural network training on the evaluation and prediction performance of artificial neural networks. The research centers on a magneto hydrodynamic flow model (RHMT-VSCR) that depicts the movement of rotating fluid along a vertical sheet in a permeable medium. Furthermore, the model considers the impact of heat source-sink interactions, thermal radiation, and reactive species in conjunction with the effects of Hall current on the enhancement of energy and solute profiles. Because the induced magnetic field has a negligible magnetic Reynolds number, it is disregarded. A set of governing nonlinear PDEs is converted to a system of ODEs by applying an appropriate postulate of similarity variables in order to analyze the system. The multilayer perceptron network utilizes a supervised Levenberg–Marquardt Backpropagation algorithm (LMLA-BPNN) to ascertain the ideal quantity of neurons to be included in the hidden layer of artificial neural networks intended for modeling purposes. The bvp4c numerical approach is utilized to establish a continuous neural network mapping, which produces datasets that are utilized for the purposes of authentication, training, and testing. The range i.e., 10−2−10−8 of absolute error of the reference and target data demonstrates the optimal accuracy performance of LMLA-BPNN networks. After acquiring knowledge of neural network mapping, it is applied to approximate solutions for a wide range of scenarios through the manipulation of physical constraints, including suction/injection quantities, magnetic parameter, and porosity parameter, which influence the characteristics of flow, energy, and concentration.To assess the precision of the proposed method, statistical graphs based on regression, mean squared error analysis graphs, and error histogram graphs are employed. The results of the research demonstrate that the Levenberg-Marquardt Backpropagation neural network mappings' derivation, convergence, authentication, and stability were effectively validated.

Fluctuations in abundance of the striped venus clam Chamelea gallina in the southern Adriatic Sea (Central Mediterranean Sea): knowledge, gaps and insights for ecosystem-based fishery management

An assessment on the fluctuations in abundance of the striped venus clam (Chamelea gallina) in the southern Adriatic Sea (Central Mediterranean Sea), and the northern Gargano area, has been conducted through both historical information and recent data from monitoring surveys during the period 1997–2019. Production trends, conditions of the commercial stock biomass, and depth distribution pattern of juveniles and commercial sizes were analysed testing temporal differences. Moreover, the exploitation of the clam beds and recruitment events were investigated in 2018–2019. Changes in abundance were analysed using non-parametric tests for both juvenile (length class, LC < 22 mm) and commercial (LC ≥ 22 mm) fractions. Hydrodynamic changes, temperature and salinity variations were explored using a 3D hydrodynamic numerical model (MIKE 3 FM-HD) and statistical analysis, as well as changes in benthic assemblages impacted by hydraulic dredges were investigated through PERMANOVA and other multivariate analysis.The results showed a temporal decline of production and biomass of C. gallina during the 1997–2019 period, and a regression of the depth limit in the clams’ distribution towards shallower waters. A significant reduction in juveniles was observed during 2018–2019 with a very limited recruitment. The fishing exploitation showed high impacts on the commercial stock and benthic assemblages in the summer of 2018. Overall, water currents were predominantly directed offshore in 2018, during the C. gallina spawning period. This could affect the larval dispersal and settlement on unsuitable bottoms. Anomalies in temperature (high peaks in August 2018, > 28 °C) and salinity (low values in spring 2018, < 37 PSU) could have induced stress and mortality events on the entire clam bed in the study area. This first study highlights the need to integrate environmental information in the assessment of commercial stocks of clams in the Adriatic Sea, to better understand climate change effects on the fluctuations and to support effective ecosystem-based fishery management.