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This study tackles the long-term problem of continuous variable crown (CVC) rolling mills' inadequate hot-rolled strip edge drop control capability, which is a major barrier to raising product quality. This work thoroughly examines the mechanism of edge drop using a coupled model of the roll system and rolling piece to obtain a deeper understanding of the factors causing edge drop in hot-rolled strips. Then, a universal design approach for the Symmetrical Variable Taper Plus (SVT +) roll contour is proposed. This advanced roll contour technology is capable of enhancing edge drop control across strips of varying widths by making precise corrections to the CVC curve at specific locations. In order to further refine the process, a multi-objective roll contour parameter optimization strategy is introduced. This strategy is designed to decouple strip crown control from edge drop control, thereby enabling more precise adjustments. In addition, this study presents an in-depth examination of the edge drop control characteristics of the proposed SVT + through simulation experiments under both no-load and on-load conditions. The results confirm the effectiveness of SVT + in reducing strip edge drop under a variety of conditions. Results from industrial experiments further highlight the potential of SVT + , demonstrating a relative decrease in strip edge drop of 46.44% and an enhancement of 22.72% in the strip crown qualification rate. These improvements are particularly beneficial for the qualification rate of strip products with a small target crown. [ABSTRACT FROM AUTHOR]

Cities place a high priority on addressing urban flooding issues and have worked on flood prevention planning and construction efforts. This study aims to develop the improved coupling hydrologic-hydrodynamic model based on SWMM and TELEMAC-2D model by considering river runoff factors. Taking Tongzhou district of Beijing as an example, two different coupled models of the drainage network are constructed for comparison. The research focused on the drainage capacity of the study area and surface ponding water under different rainfall recurrence periods to evaluate the current flood resilience status and the priority of drainage network improvements. The results indicate that the demonstration area effectively mitigates urban flooding and can handle a 100-year return period rainfall event, with a maximum inundation depth of 0.407 m and an overflow node ratio of 20.8%. As the rainfall recurrence period increases, the number of overflow nodes tends to stabilize. Due to the high susceptibility of traffic hubs in cities to flooding, the result of contrast model analysis suggests prioritizing the drainage networks under main roads and overpasses and implementing Low Impact Development (LID) facilities around rivers to enhance urban infiltration and reduce river overflow risks. This coupled model demonstrates good applicability and high simulation accuracy for complex urban flood scenarios, emphasizing the importance of targeted urban planning and infrastructure improvements in enhancing flood resilience. [ABSTRACT FROM AUTHOR]

This paper introduces a continuous finite element model to simulate fluid flow-bedform interaction problems. The approach utilizes a non-oscillatory finite element algorithm to compute the fluid dynamics by solving the complete Navier–Stokes equations. Additionally, it addresses the evolution of the fluid–bedform interface as a consequence of spatially non-balanced sediment fluxes through the solution of a conservation equation for the erodible layer thickness. A sign preservation algorithm is particularly relevant for landform tracking because a positive definite thickness of the erodible sediment layer is essential to model the interaction between evolving cohesionless sediment layers and rigid beds. The fluid/terrain interface is explicitly captured through a surface tracking methodology. First, new nodes fitting the interface are incorporated into the finite element mesh; then, elements beneath this interface are deactivated, while intersected elements are restructured to get a mesh composed exclusively of tetrahedral elements. Numerical experiments demonstrate capabilities of the method by exploring relevant problems related with civil engineering, such as the evolution of trenches and the scour of a submerged pile. [ABSTRACT FROM AUTHOR]

Rainfall, evaporation, tides and waves make the soil at coastlines show dynamic unsaturated characteristics. In order to cope with landslides, collapses, and coastline receding, microbially induced calcium carbonate precipitation (MICP) was recently implemented to reinforce the soil in slopes and coastal zones using a spraying method. However, most of the researches on MICP focus on soil with a static saturation degree, and there are few numerical researches about the MICP reactions under dynamic saturation degree. Therefore, a coupled numerical model capable of describing the evolutions of bacteria, substance, calcium carbonate (CaCO3), porosity, and permeability in unsaturated soil over time reasonably was developed based on the convective–diffusion–reaction theory and the Richards' equation. The effect of MICP reactions on the parameters α, n, θs, θr in van Genuchten-Mualem (VG) model was considered. A large cylinder test (30 × 75 cm) about reinforcing sand based on the spraying method was carried out to validate the model. The CaCO3 distribution of the MICP infiltration and mineralization was fully reproduced and the concept of critical depth (Zcr) was proposed. The initial porosity, initial bacterial concentration, and spraying rate were the main parameters affecting the CaCO3 distribution and critical depth Zcr. When the bacterial concentration increased, the maximum CaCO3 content, critical depth Zcr, and normalized permeability coefficient (k/k0) indicated exponential increase, exponential increase, and exponential decrease. The saturated permeability coefficient of the sand was determined by the maximum calcium carbonate. The normalized permeability coefficient (k/k0) and critical depth Zcr showed an exponential decrease and a power function increase with the increase of the maximum CaCO3 content. [ABSTRACT FROM AUTHOR]

With the breakthrough in mixing hydrogen into natural gas pipelines for urban use, the widespread application of hydrogen-blended natural gas (HBNG) in energy delivery is imminent. However, this development also introduces significant safety concerns due to notable disparities in the physical and chemical properties between methane and hydrogen, heightening the risks associated with gas leaks. Current models that simulate the diffusion of leaked HBNG from buried pipelines into the atmosphere often employ fixed average leakage rates, which do not accurately represent the dynamic nature of gas leakage and diffusion. This study uses computational fluid dynamics (CFD) 2024R1 software to build a three-dimensional simulation model under a soil–atmosphere coupling model for HBNG leakage and diffusion. The findings reveal that, in the soil–atmosphere coupling model, the gas diffusion range under a fixed leakage rate is smaller than that under a dynamic leakage rate. Under the same influencing factors in calm wind conditions, the gas primarily diffuses in the vertical direction, whereas under the same influencing factors in windy conditions, the gas mainly diffuses in the horizontal direction. [ABSTRACT FROM AUTHOR]

The electro‐osmosis approach efficiently facilitates the rapid dewatering of soil with high water content and contributes to reducing contaminant levels within the clay soil. However, the changes of chemical field caused by ion transport in the clay soil during electro‐osmosis process will also influence the clay soil consolidation effect. Existing theories predominantly tend to disregard this crucial physical process and its resultant effects, thereby restraining a comprehensive analysis of electro‐osmosis consolidation (EOC) behavior under intricate chemical conditions. This study introduces a concise model of EOC and ion transport considering chemical osmosis. The model considers the nonlinear variation of clay soil parameters such as compressibility, permeability, and effective diffusion coefficients, along with the interaction between EOC and ion transport. Meanwhile, the correctness of the model is verified from different aspects such as theoretical derivation and model comparison. Based on the proposed model, the impacts of the variation in electrical field intensity and chemical concentration on the coupled behaviors between EOC and ion transport are systematically investigated, with and without incorporating nonlinear consolidation characteristics. The results show that diffusion and electro‐migration exhibit a more pronounced effect on ion transport during EOC. Simultaneously, with the increase of ion concentration in clay soil pore solution, the effects of chemical osmosis become increasingly apparent, thereby enhancing clay soil settlement. [ABSTRACT FROM AUTHOR]

Landslide, debris flow, and other destructive natural hazards induced by heavy rainfall in mountainous regions are sometimes not independent but combined to form a disaster chain. Based on the integral link between the triggering of the landslide and the subsequent debris flow, we propose an approach that combines the transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model and the AL-A model to achieve hourly hazard prediction. The results indicate that the TRIGRS model performes well in predicting the spatial distribution of the shallow landslides, with a success rate of 57%. Thus, it is reasonable to use it as the initial input for debris flow simulations. The coupled model was found to have a good accuracy of 67.4% in predicting the debris flow. Furthermore, the proposed coupled model can dynamically predict disasters by the hour based on actual rainfall events. Therefore, the results of this study help provide a more complete hazard prediction method for rainfall- induced landslide-debris flow hazards in mountainous regions. [ABSTRACT FROM AUTHOR]

Attitude information is as important as position information in describing and localizing objects. Based on this, this paper proposes a method for object attitude sensing utilizing ultra-high frequency passive RFID technology. This method adopts a double tag array strategy, which effectively enhances the spatial freedom and eliminates phase ambiguity by leveraging the phase difference information between the two tags. Additionally, we delve into the issue of the phase shift caused by coupling interference between the two tags. To effectively compensate for this coupling effect, a series of experiments were conducted to thoroughly examine the specific impact of coupling effects between tags, and based on these findings, a coupling model between tags was established. This model was then integrated into the original phase model to correct for the effects of phase shift, significantly improving the sensing accuracy. Furthermore, we considered the influence of the object rotation angle on phase changes to construct an accurate object attitude recognition and tracking model. To reduce random errors during phase measurement, we employed a polynomial regression method to fit the measured tag phase information, further enhancing the precision of the sensing model. Compared to traditional positioning modes, the dual-tag array strategy essentially increases the number of virtual antennas available for positioning, providing the system with more refined directional discrimination capabilities. The experimental results demonstrated that incorporating the effects of inter-tag coupling interference and rotation angle into the phase model significantly improved the recognition accuracy for both object localization and attitude angle determination. Specifically, the average error of object positioning was reduced to 12.3 cm, while the average error of attitude angle recognition was reduced to 8.28°, making the method suitable for various practical application scenarios requiring attitude recognition. [ABSTRACT FROM AUTHOR]

Flash flooding has become more prominent under climate change, threatening people's life and property. Post‐event investigations of recent events emphasize the role of floating debris, such as vehicles, in exacerbating damage. Few modeling methods and tools have been developed to simulate the full‐process dynamics of floating debris driven by large‐scale flood waves in real world. In this work, a fully coupled model is developed for simulating the full‐process interactive movements of vehicles driven by flash flood hydrodynamics, from entrainment, transport to deposition. The proposed coupled modeling system consists of a finite volume shock‐capturing hydrodynamic model solving the 2D shallow water equations and a 3D discrete element method (DEM) model. The proposed two‐way coupling approach estimates the hydrostatic and hydrodynamic forces acting on solid objects using the water depth and velocity predicted by the hydrodynamic model; the resulting counter forces on the fluid flow are then considered by adding extra source terms in the hydrodynamic model. A multi‐sphere method is further embedded in the DEM model to better represent vehicle shapes. New calculation modules are further implemented to represent the vehicle entrainment, contact and stopping motions. The coupled model is applied to reproduce a flash flood event hit Boscastle in the UK in 2004. Over 100 vehicles were moved and carried downstream by the highly transient flood flow. The model well predicts the hydrodynamics, interactive transport process and the final locations of vehicles. The proposed coupled model provides a new tool for simulating large‐scale flash flooding processes, including debris dynamics. Key Points: A new coupled model for simulation of entrainment, transport and deposition of vehicles driven by and interacting with flood hydrodynamicsThe model is used to reproduce a flash flood event that moved over 100 vehicles, with results consistent with post‐event report and surveyIncreasing number of floating vehicles alters flood hydrodynamics and intensifies debris‐debris and debris‐fluid interactions [ABSTRACT FROM AUTHOR]

Natural forests play a crucial role in providing various ecosystem services, including timber production and biodiversity conservation. However, climate change and anthropogenic factors pose a severe threat to competing forest ecosystem services functions. Therefore, to optimize and sustainably utilize competing forest services, tradeoffs are often necessary. This study was conducted in Northwest China to explore tradeoffs aimed at improving the quality of Quercus wutaishanica Mayr natural forests under climate change conditions, focusing on stand volume, timber production, and understory vegetation diversity conservation. Data from 77 field surveys were used to construct a coupled model for stand growth, stand structure, and site conditions. Changes in understory vegetation species number (UVSN) with crown cover were quantified. These models and relationships can be used as tools to estimate tradeoffs. As stand density increased, single-tree volume decreased, whereas timber volume increased. UVSN increased and then decreased with increasing crown cover and was able to maintain a relative maximum at 0.5–0.65. Under the current climatic conditions, the optimum stand densities corresponding to 30, 40, 50, and 60 years were 1390, 1153, 1042, and 871 trees/ha, respectively, to maintain a high UVSN and adequate stand volume. When mean annual temperature rose, stand densities could be reduced to maintain high-quality timber. Although only two major services were considered, the tradeoffs presented in this study can inform future research to improve the quality of natural forests. [ABSTRACT FROM AUTHOR]

To provide accurate and efficient forecasting of fluvial flooding assessment in the river basin, the present study links the well-known CA-based urban inundation modeling (2D-OFM-CA) with a one-dimensional river flow model (1D-RFM) as a coupled 1D-2D river–overland modeling. Rules to delineate the geometric linking between the 1D-RFM and 2D-OFM-CA along embankments are developed. The corresponding exchanged water volume across an embankment is then computed by using the free and submerged weir flow formulas. The applicability of the proposed coupled model on fluvial flooding assessment is then assessed and compared with a well-recognized commercial software (HEC-RAS model) through an idealized fluvial case and an extensively studied real-scale fluvial case in the Severn River Basin. Based on the simulated results concerning the numerical accuracy, the coupled model is found to give similar results in the aspects of the river flow and overland flow modeling in both two study cases, which demonstrates the effectiveness of the linking methodology between the 1D-RFM and 2D-OFM-CA. From the viewpoint of numerical efficiency, the coupled model is 47% and 41% faster than the HEC-RAS model in the two cases, respectively. The above results indicate that the coupled model can reach almost the same accuracy as the HEC-RAS model with an obvious reduction in its computational time. Hence, it is concluded that the coupled model has considerable potential to be an effective alternative for fluvial flooding assessment in the river basin. [ABSTRACT FROM AUTHOR]

On ensemble‐based coupled data assimilation, cross‐component parameter estimation (CPE), has not been as extensively developed and applied as weakly coupled state and parameter estimation along with cross‐component state estimation. This discrepancy is partially attributed to the lack of emphasis on the instantaneous response of coupled model states with respect to parameters across different components. We define so‐called response as the instantaneous parameter sensitivity (IPS). Under the framework of sequential assimilation, the prior information heavily relies on the IPS of coupled states with different time scales. Based on the IPS analysis for an intermediate coupled model, a series of twin experiments of state and parameter estimation are conducted, in which an IPS‐inspired adaptive inflation scheme for parameter ensemble is introduced. Results show that the success of a parameter estimation strategy is closely tied to the significant IPS of the observed state to the parameter targeted for optimization, as it maintains a high signal‐to‐noise ratio in the error covariance between parameter and prior state, thereby enhancing parameter estimation. An interesting finding in the context of IPS‐based CPE is: an atmospheric parameter can be successfully estimated by assimilating observations from slow‐varying oceanic component, but not vice versa. In comparison with cross‐component state estimation, successful CPE significantly enhances the estimation accuracy of coupled states by mitigating model bias. Plain Language Summary: The sequential data assimilation, exemplified by the ensemble‐based methods, focuses on adjusting model state and/or parameter instantaneously. Its underlying theoretical basis lies in the fact that random fluctuations characterize the Earth system in nature. Previous studies on ensemble‐based parameter estimation concentrated on the climatological response of state to parameter. However, this study emphasizes the instantaneous impact of parameter on state, denoted as the instantaneous parameter sensitivity (IPS), which is crucial for interpretating the feasibility of cross‐component parameter estimation (CPE) in the scope of strongly coupled data assimilation (CDA). Assimilating fast‐varying atmospheric observation has been employed to estimate slow‐varying oceanic state, but it cannot be taken for granted to optimize oceanic parameter. Conversely, assimilating oceanic observation can optimize atmospheric parameter and coupling coefficient since the ocean significantly responds to their direct modulation. The IPS serves as a tool for researchers to preliminarily assess the feasibility of CPE, representing a valuable advance particularly in the realm of strongly CDA. Key Points: The instantaneous parameter sensitivity plays a crucial role in interpreting the feasibility of ensemble‐based parameter estimationThe significant instantaneous response of model state to parameter maintains a high signal‐to‐noise ratio in their error covarianceAtmospheric parameter and coupling coefficient related to ocean‐atmosphere interaction can be optimized by assimilating oceanic observation [ABSTRACT FROM AUTHOR]

A large number of experimental studies have demonstrated that the permeability and damage of rock are not constant but rather functionally dependent on stresses or stress-induced deformation. Neglecting the influence of damage and permeability evolution on rock mechanics and sealing properties can result in an overestimation of the safety and stability of underground engineering, leading to an incomplete assessment of the risks associated with surrounding rock failure. To address this, the damage and permeability evolution functions of rock under compression were derived through a combination of experimental results and theoretical analysis, unifying the relationship between porosity and permeability in both porous media flow and fractured flow. Based on this, a fluid–solid coupled seepage model considering rock damage and permeability evolution was proposed. More importantly, this model was utilized to investigate the behavior of deformation, damage, and permeability, as well as their coupled effects. The model's validity was verified by comparing its numerical results with experimental data. The analysis results show that the evolution of permeability and porosity resulted from a competitive interaction between effective mean stress and stress-induced damage. When the effective mean stress was dominant, the permeability tended to decrease; otherwise, it followed an increasing trend. The damage evolution was primarily related to stress- and pressure-induced crack growth and irreversible deformation. Additionally, the influence of the seepage pressure on the strength, damage, and permeability of the investigated rock was evaluated. The model results reveal the damage and permeability evolution of the rock under compression, which has a certain guiding significance for the stability and safety analysis of rock in underground engineering. [ABSTRACT FROM AUTHOR]

SLNE is the coupled model, that was developed in 2023. SL and NE here are the first two letters from SLAV (Semi-Lagrangian, based on Absolute Vorticity equation) model of the atmosphere and NEMO (Nucleus for European Modelling of the Ocean) ocean model that have been coupled using OASIS3-MCT software. The initial conditions for SLAV and NEMO are specified from an atmospheric and ocean analyses produced in Hydrometcentre of Russia. The 2010–2021 hindcast accuracy study shows, that SLNE has comparable errors to the operational SLAV model on a sub-seasonal time scale. The SLNE model has improved prediction skill of the 2010 heatwave features in comparison to SLAV, that is a motivation for further work to improve the coupled model. [ABSTRACT FROM AUTHOR]

The atmosphere‐ocean is a highly coupled system with significant diurnal and hourly variations. However, current coupled models usually lack sub‐diurnal scale processes at the air‐sea interface due to the finite vertical resolution for ocean discretization. Previous modeling studies showed that sub‐diurnal scale air‐sea interaction processes are important for ocean mixing. Here, by designing an integrated sub‐diurnal parameterization (ISDP) scheme which combines different temperature profiling functions, we stress sub‐diurnal air‐sea interactions to better represent the local ocean mixing. This scheme has been implemented into two coupled models which contributed to the Climate Model Intercomparison Project (CMIP), referenced by the Intergovernmental Panel on Climate Change—Community Earth System Model and Coupled Model version 2. The results show that the ISDP scheme improves model simulations with better climatology and more realistic spectra, especially in the tropics and North Pacific Ocean. With the scheme, the tropical cold tongue bias is significantly relaxed by reducing the overestimation of ocean upper mixing, and the cold bias of North Pacific Ocean is reduced due to the improvement on currents and net heat fluxes. Our scheme may help better the simulation and prediction skills of coupled models when their horizontal resolution becomes fine but vertical resolution remains relatively coarse as it describes high‐frequency air‐sea interactions more realistically. Plain Language Summary: The atmosphere and ocean interact with each other. In these interactions, changes may occur over different time periods. Some changes take years or months, while others happen in days or hours. The atmosphere changes quickly throughout the day, such as air temperature, wind, and rain. These quick changes in the atmosphere can affect the ocean rapidly. Similarly, there are quick changes in the ocean. These quick changes also affect the atmosphere in return. Understanding these quick changes is important. However, it is difficult to perfectly capture the quick changes in the climate models because they do not always represent the ocean behavior accurately. In this study, we developed a new scheme (named the sub‐diurnal scale parameterization, ISDP) to better represent these quick changes. We added this new scheme into two widely‐used climate models. These models are important tools for studying climate change. Our new scheme represents better the ocean mixing and interaction based on the local weather conditions. When we use ISDP, the climate models get better at simulating climate. They're more accurate in showing ocean temperatures in the tropics. These models make the tropical oceans seem colder than they really are, but our scheme, to some extent, fixes this problem. The results also show the more accurate ocean temperatures in the North Pacific Ocean. Our new scheme has a great potential to make climate models more accurate. Key Points: An integrated sub‐diurnal scale parameterization (ISDP) scheme has a more appropriate representation for local ocean mixingThe ISDP scheme has been implemented into two models which contributed to the Climate Model Intercomparison Project, referenced by IPCC: Community Earth System Model and Coupled Model version 2The model tropical cold tongue bias with ISDP is relaxed by reducing the overestimation of ocean upper mixing [ABSTRACT FROM AUTHOR]

Affected by climate and topographic conditions, Zhengzhou has experienced frequent extreme rainstorms and serious flood disasters in history. It is one of the 31 key flood control cities announced by the National Flood Prevention Office. MIKE series models were adopted to construct a flood simulation model for Zhengzhou based on key technical issues such as simulation of urban rainfall and flow generation, simulation of large regional confluence and flood evolution, and simulation of urban underground pipe network drainage, by considering the influence of complex structures and river network of inland river system. The model was calibrated and validated using the measured rainstorm and flood data in 2011, 2015 and 2021. The results show that the model simulation effect is good, and the calculated results are not much different from the actual measurement, which can be used for flood simulation evaluation in Zhengzhou. [ABSTRACT FROM AUTHOR]

The high-speed penetration of concrete targets by kinetic energy projectiles results in apparent mass loss, which blunts the nose of the projectile and decrease its penetration performance. The friction work between the projectile and the concrete target, the plastic deformation of the projectile, and the cutting of aggregates to the projectile significantly affect the mass loss of the projectile. To address these effects, a discrete iterative model is developed for the mass loss and nose shape evolution of the projectile by coupling three mechanisms based on the effect of temperature on strength. In the model, both friction work and plastic work increase the temperature of the projectile’s surface layer, thereby weakening the strength of this part and rendering it easier for mass loss to occur due to aggregate cutting. The model discretizes the projectile and penetration process with respect to the space and time dimensions, respectively. The mass loss and nose shape evolution of the projectile are obtained by iteratively calculating a point-by-point regression. The predicted depth of penetration (DOP), mass loss, and residual projectile profile are compared with experimental data to validate the model. The comparison shows satisfactory agreement between the calculated results and experimental data. Additionally, the deceleration, velocity, DOP, and mass loss during penetration are analyzed with respect to time. Finally, based on the model, the effects of projectile strength, caliber-radius-head (CRH), and concrete target strength on penetration are discussed. [ABSTRACT FROM AUTHOR]

While there is huge demand for regional forecasts, information needed for selection of the most appropriate temporal and spatial scales is not available. The objective of this study is to demonstrate the basis of forecasting monthly mean rainfall over homogeneous regions by analyzing the forecasting skill and source of predictability. Reforecasts generated at the National Center for Medium Range Weather Forecasting (NCMRWF) for the period 1993–2015 using the coupled Unified Model are used in this study. Analysis of the forecasting skill over increasingly large lead times, averaging periods and spatial scales, is carried out to compare the skill at different time‐scales and to highlight the effect of spatial averaging over regions of coherent rainfall characteristics. Analysis of probabilistic forecasts is carried out to further demonstrate the usefulness of monthly mean forecasts. The influence of forcings on rainfall is studied both in model and in observations to understand the model's skill in representing interannual variability of monthly mean rainfall. Multiple regression analyses carried out for rainfall using climate indices as independent variables shows that the extent of forcings can largely explain the high variability of rainfall during the onset and withdrawal phase compared to the peak phase of monsoons. ENSO‐related subsidence is found to influence mainly the southern peninsular region, while tropical sea surface temperatures (SSTs) in the Indian Ocean are found to influence rainfall over northwest and central India by forcing circulation patterns typically associated with circumglobal teleconnections (CGTs) which are strongest during the month of June. Interestingly, the influence of CGTs on rainfall in the northeast is opposite to its influence on other homogeneous regions, which explains the contrast in influence of the North Indian Ocean SSTs on rainfall over the northeast and over All India. The model representation of influence of forcings and strength of teleconnections is better for specific region–month pairs, which is seen to influence the monthly variations in skill of forecasting rainfall over homogeneous regions. [ABSTRACT FROM AUTHOR]

The southwest monsoon onset over Kerala (MOK) is very crucial for an Agricultural country like India hence its prediction in the extended range time scale (about 3 weeks in advance) is very useful for the Kharif season in India. As the declaration of MOK involves subjective interpretation of the forecasters, an objective method of prediction of MOK based on dynamical models could successfully avoid bogus onsets. Two objective prediction methods for MOK are developed based on the real-time extended range forecast (ERF) of rainfall measured over Kerala coast 080-120N, 740-780E and the strength and depth of the westerly wind over the Arabian Sea (050-120N, 550-750E) for the period from 2003 to 2022 are used in the first method. In addition to these 3 indices, meridional pressure gradient along the west coast of India is used in the second method with 4 indices. The MOK date is defined objectively based on these variables exceeding the thresholds in both the methods. The results indicate that the MOK forecast with four indices performed well compared to that with three indices during the whole period from 2003 to 2022 with the mean deviation days of MOK found to be 0.75 and 3.05 days respectively. Overall, the dynamically defined onset date over Kerala based on the real-time ERF indicated useful skill at least about 2–3 weeks in advance. It is also demonstrated that the district-level Multi-Model Ensemble forecast in the medium range (5 days in advance) based on 5 global models can add value to the categorical ERF of MOK for the exact forecast date of MOK.Article Highlights: The objective method for prediction of monsoon onset date over India in extended range time scale is presented. The extended range prediction of onset based on dynamical model shows useful skill up to 2 to 3 weeks. Combining the extended range forecast of onset with medium range is helpful for predicting the exact onset date. [ABSTRACT FROM AUTHOR]

In this paper we use the weighted discontinuous Galerkin finite element method to solve the dual-porosity-Brinkman coupling model. The dual-porosity model describes fluid flow in a dual-porosity medium composed of matrix and microfractures, while the Brinkman equation describes fluid flow in hydraulic fractures or conduits containing "debris filling" or "proppant filling". The two models are coupled by the four physically effective interface conditions, which are constructed based on the fundamental properties of the dual-porosity model and the Brinkman-Darcy model. We provide a weighted discontinuous discrete scheme for the model and derive the optimal error estimates. Through numerical experiments, we verify the properties of the model and the advantages of the numerical method, such as the optimal convergence rate of the numerical solution and the simulation of the flow characteristics around hydraulic fractures and conduits. [ABSTRACT FROM AUTHOR]

In the 1D–2D coupled simulation of urban waterlogging, the calculation process of vertical flow exchange is independent from the 1D hydraulic calculation, resulting in a failure to consider the node head and pipe flow during the exchange flow calculation, which may lead to irrational results and further affect the stability of the model calculation. However, setting an upper limit for the exchange flow may introduce excessive subjective factors into the simulation process. In this study, a vertical flow exchange method based on the water balance of nodes is proposed. When a node is in an overloaded state, the calculation of vertical flow exchange at the node is integrated into the 1D hydraulic simulation process, thus taking into consideration the influence of the node head and pipe flow when calculating vertical flow exchange. Additionally, the iterative solution method used in the 1D hydraulic model ensures numerical harmony between the vertical flow exchange, node head and pipe flow, thus ensuring the stability of the coupled calculation. For the non-overloaded nodes, the calculation of the vertical flow exchange was conducted using a variable-head orifice discharge formula, enabling the consideration of changes in the surface water depth during the calculation of the node backflow. Using the InfoWorks ICM model as a benchmark, a comparative analysis of case simulation results demonstrated that the improved vertical flow exchange method was able to accurately and stably simulate the process of vertical flow exchange. When used with the improved vertical exchange method, the coupled model gave simulation results that closely matched those of the benchmark model. [ABSTRACT FROM AUTHOR]

Abstract On ensemble‐based coupled data assimilation, cross‐component parameter estimation (CPE), has not been as extensively developed and applied as weakly coupled state and parameter estimation along with cross‐component state estimation. This discrepancy is partially attributed to the lack of emphasis on the instantaneous response of coupled model states with respect to parameters across different components. We define so‐called response as the instantaneous parameter sensitivity (IPS). Under the framework of sequential assimilation, the prior information heavily relies on the IPS of coupled states with different time scales. Based on the IPS analysis for an intermediate coupled model, a series of twin experiments of state and parameter estimation are conducted, in which an IPS‐inspired adaptive inflation scheme for parameter ensemble is introduced. Results show that the success of a parameter estimation strategy is closely tied to the significant IPS of the observed state to the parameter targeted for optimization, as it maintains a high signal‐to‐noise ratio in the error covariance between parameter and prior state, thereby enhancing parameter estimation. An interesting finding in the context of IPS‐based CPE is: an atmospheric parameter can be successfully estimated by assimilating observations from slow‐varying oceanic component, but not vice versa. In comparison with cross‐component state estimation, successful CPE significantly enhances the estimation accuracy of coupled states by mitigating model bias.

Precise long-term runoff prediction holds crucial significance in water resource management. Although the long short-term memory (LSTM) model is widely adopted for long-term runoff prediction, it encounters challenges such as error accumulation and low computational efficiency. To address these challenges, we utilized a novel method to predict runoff based on a Transformer and the base flow separation approach (BS-Former) in the Ningxia section of the Yellow River Basin. To evaluate the effectiveness of the Transformer model and its responsiveness to the base flow separation technique, we constructed LSTM and artificial neural network (ANN) models as benchmarks for comparison. The results show that Transformer outperforms the other models in terms of predictive performance and that base flow separation significantly improves the performance of the Transformer model. Specifically, the performance of BS-Former in predicting runoff 7 days in advance is comparable to that of the BS-LSTM and BS-ANN models with lead times of 4 and 2 days, respectively. In general, the BS-Former model is a promising tool for long-term runoff prediction. HIGHLIGHTS The effectiveness of a Transformer model for simulating and predicting long-term daily runoff is explored.; The response of the Transformer model to prior hydrological knowledge in base flow separation is analyzed.; The potential of base flow separation techniques to improve the ability to predict the runoff lead time in deep learning models is explored.;

Due to the complex cross-section and scale effects, surface and internal defects are prone to occur in the ultra-large-section beam blank. In this study, a coupled model of steel liquid flow and heat transfer within a 1300 × 510 × 140 mm cross-section beam blank mould was established. The results indicate that single-port SEN reduced the flow activity on the meniscus, and the three-ports SEN led to significant high temperature zones and re-melting of the solidified shell in the flange tip and web. The four-ports nozzle not only optimizes the internal flow behavior of the mould but also enhances the uniformity of temperature and solidification. The maximum circumferential difference in shell thickness under the four-ports SEN was only 8.1 mm, compared to 13.2 mm and 13.8 mm under the single-port and three-ports SEN, respectively.

Stand transpiration (T) is an important process in the forest hydrological cycle, influenced by environmental factors such as potential evapotranspiration (PET) and relative extractable water (REW). Clarifying the independent effects and interactions of environmental factors on T can help to better understand the mechanisms of ecohydrological control of forest water use. In this study, the independent contributions of PET and REW to T and their interactions were quantified through field observations, modeling, and factor analysis in the secondary birch forest of the southern Greater Khingan Mountains. First, observations were made of sap density, meteorological variables, and REW over three growing seasons. Second, a T-coupled model (R² = 0.68, NSE = 0.7) was developed based on long-term observations of T, PET, and REW. Finally, the factorial analysis showed that PET was the main driver affecting T changes compared to REW and the interaction between PET and REW. The relative contribution of PET to T was 7.8%, 11.1%, and 10.7% in 2017, 2018, and 2019, respectively. REW limited 1.8%, 12.3%, and 9.7% of T change in 2017, 2018, and 2019, respectively, compared to the mean of these three years. Our study provides a simple and feasible way to separate the effects of PET and REW on T change and may deepen the understanding of the effects of different environmental factors on T.

Previous studies on the co-evolving between vaccination strategies and epidemics mainly assumed that the vaccination strategies were made in the period between two spreading seasons. However, individual cognition during the spreading seasons might also alter the vaccination strategy and inversely influence the epidemic spreading. We propose a coupled disease-behavior model to describe the dynamic evolution of vaccination behavior during the spread of infectious diseases. The model integrates a susceptible-infected-vaccinated (SIV) model with the diffusion of vaccination behavior. We focus on the trade-off between perceptions of infection risk and the vaccination behaviors of neighbors, characterizing individual vaccination opinions. We introduce an opinion-critical value to map vaccination opinions into vaccination behavior. The vaccination coverage of the disease-behavior model is studied in network models and real-world networks. In addition, when societal costs are measured based on the degree of initial vaccinees, the cost of randomly selecting initial vaccinees is lowerthan selecting individuals with high or low degrees as vaccinees. Evaluating an individual's ability to transmit vaccination behavior based on the neighbor's number is inappropriate. We find that the impact of effective spreading rates on group vaccination is not one-sided and that reducing fear and highlighting the dangers of infectious diseases are crucial to increasing vaccination coverage. [ABSTRACT FROM AUTHOR]

Slope instability is a common type of damage in embankment dams. Analyzing its microstructural changes during water transport is beneficial to identify the critical damage point in more detail. To this end, we closely link both diffused water molecule and damaged concrete. On the basis of the original research on fractal theory, the fractal permeability model for the pore system is established. At the same time, considering the pore structure characteristics of concrete, the models for fluid–solid coupling inside and outside the embankment are established in this work. The simulated results and experimental data agree well, thus verifying the correctness of the proposed models. The changes of concrete pore structures under different water pressure and different initial porosities are simulated by numerical methods. The results show that: (1) with the increase of the safety factor, the slope of the embankment begins to be damaged at the critical point and then completely destabilized; (2) with the increase of the pressure head, the change of the fractal dimension of the embankment's porosity from the top to the bottom changes from linear to nonlinear. (3) The initial porosity of concrete is proportional to the evolution of concrete pore structure. From a technical point of view, this study can contribute the effective technical guidance for related professional practitioners in the analysis of embankment slope stability from a microscopic point of view. [ABSTRACT FROM AUTHOR]

In order to accurately understand the dynamic behavior of the machine tool spindle, it is necessary to accurately model the interactions between thermal, nonlinear dynamics and nonlinear milling process for machine tool spindle. To this end, this paper establishes a real-time coupled model for the thermal–dynamics–milling process of spindle considering nonlinear characteristics, and the established model can be used to predict response evolution, including temperature distribution, thermal deformation, vibration, bearing support force and instantaneous milling loads. Using the thermal network method, a transient thermal model of the spindle system is established considering the time-varying characteristics of heat generation and thermal transfer during milling. The five degree of freedom (DOF) nonlinear dynamic model of bearing is established including thermal deformation and is coupled with spindle vibrations. The ten-DOF Timoshenko beam is used to model the spindle dynamics with the tool subjected to nonlinear dynamic milling load. The instantaneous load generated in milling process is calculated including the effects of tool vibration, cutting condition and the geometric errors of tool assembly. Besides, the coupling calculation of the established model is proposed with the application of the combined fourth-order Runge–Kutta and Newmark β methods. The process dynamic responses of the actual spindle are measured, and the measured results closely match the simulation results. Finally, in order to provide theoretical reference for designers, the changes in thermal behavior, vibration and cutting stability by varying rotation speed, thermal boundary conditions and operation conditions are investigated. [ABSTRACT FROM AUTHOR]

This study investigates the impact of warm core eddies (WCEs) on the ocean response and intensity of tropical cyclones (TCs) in the Northwest Pacific, focusing on three typhoons in 2018: Jebi, Trami, and Kong-rey. The research uses the Hurricane Weather Research and Forecast (HWRF) model coupled with the MPIPOM-TC ocean model. Idealized WCEs are embedded into the ocean model ahead of each TC. The impacts of WCEs are evaluated by comparing simulations with and without their presence. Uncoupled experiments with the fixed sea surface temperature (SST) serve as a reference for TC maximum potential intensity. To quantitatively assess the impact of WCEs on the SST, enthalpy fluxes, and TC intensity, a Maximum WCE Potential Index (MWPI) is introduced. Our findings indicate that for a WCE with a 200 km radius, the potential to reduce SST cooling ranges from 34 to 37%, while the potential to increase enthalpy fluxes varies between 25 and 39%. The influence of WCEs on TC intensity, as measured by minimum pressure, shows a larger variation from 27% to 48%, depending on the oceanic and atmospheric environmental conditions in each storm. Additional experiments reveal the sensitivity of the MWPI to WCE size, with TC Trami showing less sensitivity due to its slower translational speed. This study underscores the significant role of oceanic thermal conditions, particularly WCEs, in modulating TC intensity. [ABSTRACT FROM AUTHOR]

The occurrence of landslide disasters is progressive, and evaluating the susceptibility of landslides is a prerequisite for disaster prevention and reduction. The Wangcang County, Sichuan Province is taken as an example and the frequency ratio method is used to determine the landslide sensitivity of 12 landslide impact factors in each grading interval. Through the band set statistics, 11 landslide impact factors are determined as landslide susceptibility evaluation factors. By establishing a logistic regression support vector machine (LR-SVM) coupling model, a landslide susceptibility evaluation system is established, completing the evaluation of landslide susceptibility in Wangcang County and comparing model accuracy. The results show that the evaluation index results of the LR-SVM coupling model are better than those of the logistic regression model, and the susceptibility zoning results are more reasonable and the prediction accuracy is higher. Selecting non-landslide points in low risk areas has a significant effect on improving the evaluation performance of landslide susceptibility. The sensitivity of roads, elevations, and NDVI in the study area to landslide development is strong. High risk areas are mainly distributed in low altitude water systems and on both sides of roads. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cells (PEMFCs) have emerged as a key technology in harnessing the potential of hydrogen energy. However, to fulfill the demands of efficient oxygen reduction kinetics, PEMFCs must exhibit exceptional capabilities in gas-liquid mass transfer, which is complex and challenging. This study draws inspiration from the structure of tongue skeletal muscle and mucosa, a biomimetic design for flow channel surface properties is proposed, and the intricate relationship between gas-liquid transport and cell performance is explored. Validate using experimental polarization curves and dynamic gas-liquid transport characteristics in the cathode flow channel. Results indicate that the hydrophilicity/hydrophobicity of channel walls significantly influences performance and flow characteristics. The biomimetic design outperforms conventional channels, demonstrating a 67.92% faster drainage. Notably, current density (CD) and peak power density (PD) reach 1258.0 mA/cm2 and 468.0 mW/cm2, respectively, highlighting effective performance enhancement and providing valuable insights for PEMFC optimization. • A wall wettability design inspired by the tongue skeletal muscle is proposed. • Comprehensive utilization of wall wettability can ensure uniform mass transfer. • The drainage rate of the bionic flow channel was increased by 67.92%. • The innovative work showing the 1258.0 mA/cm2 limited CD and 468.0 mW/cm2 peak PD. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The role of excitatory interneurons (EINs) in the cortical has received increasing attention in the discussion of absence seizures. Numerous physiological experiments have confirmed the correlation between EIN and absence seizures. However, the dynamic mechanisms underlying this relationship are not well understood, and there are some challenges in selecting appropriate stimulation strategies for pyramidal clusters. In this study, we incorporated EIN into the previous Taylor model and developed an improved thalamocortical coupled model consisting of ten neuronal populations. Initially, we investigated the excitatory induction effect of EIN to pyramidal clusters and the external input of EIN. Then, four different targeted treatment approaches (deep brain stimulation (DBS), current balanced biphasic pulse (CBBP), 1:0 coordinated resetting stimulation (1:0 CRS), and 3:2 CRS) were applied to the pyramidal clusters. Moreover, we established two quantitative indices to evaluate the stimulation effects. The results showed that modifying the external input of EIN and the coupling strength projected onto the pyramidal clusters can effectively transition the system from an absence seizure state to other normal states. Additionally, inputs from the left compartment were found to reduce the generation of abnormal discharge regions in the right compartment. Furthermore, considering the treatment effects and current consumption, the 3:2 CRS stimulation strategy appeared to be the most suitable treatment approach for the pyramidal clusters. This work introduces a novel coupled model containing EIN, which contributes new theoretical foundations and insights for the future treatment of absence seizures. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University / Dongnan Daxue Xuebao is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The atmosphere‐ocean is a highly coupled system with significant diurnal and hourly variations. However, current coupled models usually lack sub‐diurnal scale processes at the air‐sea interface due to the finite vertical resolution for ocean discretization. Previous modeling studies showed that sub‐diurnal scale air‐sea interaction processes are important for ocean mixing. Here, by designing an integrated sub‐diurnal parameterization (ISDP) scheme which combines different temperature profiling functions, we stress sub‐diurnal air‐sea interactions to better represent the local ocean mixing. This scheme has been implemented into two coupled models which contributed to the Climate Model Intercomparison Project (CMIP), referenced by the Intergovernmental Panel on Climate Change—Community Earth System Model and Coupled Model version 2. The results show that the ISDP scheme improves model simulations with better climatology and more realistic spectra, especially in the tropics and North Pacific Ocean. With the scheme, the tropical cold tongue bias is significantly relaxed by reducing the overestimation of ocean upper mixing, and the cold bias of North Pacific Ocean is reduced due to the improvement on currents and net heat fluxes. Our scheme may help better the simulation and prediction skills of coupled models when their horizontal resolution becomes fine but vertical resolution remains relatively coarse as it describes high‐frequency air‐sea interactions more realistically.

CH4 production rate of coalbed methane (CBM) well decreases rapidly during primary recovery in the deeply buried coal seam, resulting in a lot of CH4 residues. CO2 pour into deep coal seam with high stress sensitivity is available for enhancing CH4 recovery by improving permeability for reservoir fracture and displacing CH4 adsorbed in matrix. A coupled adsorp-hydro-thermo-mechanical (AHTM) model for deep methane development is established by considering the coupling relationships of non-isothermal and non-constant pressure competitive adsorption between CO2 and CH4, multi-phase flow, unsteady diffusion, heat transmission and in-situ stress variety. The model is verified by historical production and then used for CO2 enhanced CBM (CO2-ECBM) of deep coal reservoir in a sedimentary basin in Northwest China. The simulation results show that: (1) For primary recovery, permeability in coal reservoir drops rapidly with the development of CBM, which seriously restricts the production of CH4. The permeability of the reservoir decreases from 7.89 × 10−16 m2 to less than 1.50 × 10−16 m2, CH4 production rate in CBM well reduces to below 2000 m3/d, and the average total CH4 content of coal reservoir is reduced by 5.49 m3/t with the decrease of only 1.12 m3/t of average adsorbed CH4 in a production duration of 2000 d (2) With 10 MPa CO2 continuous injection into coal seam after 700d of primary, the permeability for reservoir and CH4 production rate increase while the total CH4 content and adsorption CH4 content in reservoir decrease compared with the primary recovery. (3) CO2 pouring into coal reservoir increases the CH4 production time and rate, which improves CH4 recovery of coal reservoir. And it increases by 23.36 %, 23.07 % and 22.46 % with shut-in thresholds of CH4 production rate of 1000 m3/d, 800 m3/d and 600 m3/d, respectively. The investigation is of great significance for the development of deep coalbed methane.

The role of excitatory interneurons (EINs) in the cortical has received increasing attention in the discussion of absence seizures. Numerous physiological experiments have confirmed the correlation between EIN and absence seizures. However, the dynamic mechanisms underlying this relationship are not well understood, and there are some challenges in selecting appropriate stimulation strategies for pyramidal clusters. In this study, we incorporated EIN into the previous Taylor model and developed an improved thalamocortical coupled model consisting of ten neuronal populations. Initially, we investigated the excitatory induction effect of EIN to pyramidal clusters and the external input of EIN. Then, four different targeted treatment approaches (deep brain stimulation (DBS), current balanced biphasic pulse (CBBP), 1:0 coordinated resetting stimulation (1:0 CRS), and 3:2 CRS) were applied to the pyramidal clusters. Moreover, we established two quantitative indices to evaluate the stimulation effects. The results showed that modifying the external input of EIN and the coupling strength projected onto the pyramidal clusters can effectively transition the system from an absence seizure state to other normal states. Additionally, inputs from the left compartment were found to reduce the generation of abnormal discharge regions in the right compartment. Furthermore, considering the treatment effects and current consumption, the 3:2 CRS stimulation strategy appeared to be the most suitable treatment approach for the pyramidal clusters. This work introduces a novel coupled model containing EIN, which contributes new theoretical foundations and insights for the future treatment of absence seizures.

The loss of anchoring force is one of the problems to be solved urgently. The anchorage loss is a key factor causing the failure of anchoring engineering, so it is crucial to study the time-dependent variation of anchoring force. Alternating dry and wet (D-W) conditions have a significant effect on deformation of rock. The anchoring system is composed of anchoring components and rock mass, and thus rock deformation has a significant impact on the loss of anchoring force. Quantifying rock deformation under the effects of D-W cycles is a prerequisite to understanding the factors that influence loss of anchoring force in anchor bolts. In this study, we designed an anchoring device that enabled real-time monitoring of the variation in strain during D-W periods and rock testing. Nuclear magnetic resonance (NMR) measurements showed that under D-W conditions, the increment in porosity was smaller for prestressed rock than unstressed rock. The trends of prestress loss and strain variation are consistent, which can be divided into three characteristic intervals: rapid attenuation stage, slow attenuation stage and relatively stable stage. At the same stress level, the rate of stress loss and strain for the soaking specimen was the highest, while that of the dried specimen was the lowest. In the same D-W cycling conditions, the greater the prestress, the smaller the strain loss rate of the rock, especially under soaking conditions. The characteristics of pore structure and physical mechanical parameters indicated that prestress could effectively suppress damage caused by erosion related to D-W cycles. The study reveals the fluctuation behavior of rock strain and prestress loss under D-W conditions, providing a reference for effectively controlling anchoring loss and ideas for inventing new anchoring components.

With the breakthrough in mixing hydrogen into natural gas pipelines for urban use, the widespread application of hydrogen-blended natural gas (HBNG) in energy delivery is imminent. However, this development also introduces significant safety concerns due to notable disparities in the physical and chemical properties between methane and hydrogen, heightening the risks associated with gas leaks. Current models that simulate the diffusion of leaked HBNG from buried pipelines into the atmosphere often employ fixed average leakage rates, which do not accurately represent the dynamic nature of gas leakage and diffusion. This study uses computational fluid dynamics (CFD) 2024R1 software to build a three-dimensional simulation model under a soil–atmosphere coupling model for HBNG leakage and diffusion. The findings reveal that, in the soil–atmosphere coupling model, the gas diffusion range under a fixed leakage rate is smaller than that under a dynamic leakage rate. Under the same influencing factors in calm wind conditions, the gas primarily diffuses in the vertical direction, whereas under the same influencing factors in windy conditions, the gas mainly diffuses in the horizontal direction.

Attitude information is as important as position information in describing and localizing objects. Based on this, this paper proposes a method for object attitude sensing utilizing ultra-high frequency passive RFID technology. This method adopts a double tag array strategy, which effectively enhances the spatial freedom and eliminates phase ambiguity by leveraging the phase difference information between the two tags. Additionally, we delve into the issue of the phase shift caused by coupling interference between the two tags. To effectively compensate for this coupling effect, a series of experiments were conducted to thoroughly examine the specific impact of coupling effects between tags, and based on these findings, a coupling model between tags was established. This model was then integrated into the original phase model to correct for the effects of phase shift, significantly improving the sensing accuracy. Furthermore, we considered the influence of the object rotation angle on phase changes to construct an accurate object attitude recognition and tracking model. To reduce random errors during phase measurement, we employed a polynomial regression method to fit the measured tag phase information, further enhancing the precision of the sensing model. Compared to traditional positioning modes, the dual-tag array strategy essentially increases the number of virtual antennas available for positioning, providing the system with more refined directional discrimination capabilities. The experimental results demonstrated that incorporating the effects of inter-tag coupling interference and rotation angle into the phase model significantly improved the recognition accuracy for both object localization and attitude angle determination. Specifically, the average error of object positioning was reduced to 12.3 cm, while the average error of attitude angle recognition was reduced to 8.28°, making the method suitable for various practical application scenarios requiring attitude recognition.

To provide accurate and efficient forecasting of fluvial flooding assessment in the river basin, the present study links the well-known CA-based urban inundation modeling (2D-OFM-CA) with a one-dimensional river flow model (1D-RFM) as a coupled 1D-2D river–overland modeling. Rules to delineate the geometric linking between the 1D-RFM and 2D-OFM-CA along embankments are developed. The corresponding exchanged water volume across an embankment is then computed by using the free and submerged weir flow formulas. The applicability of the proposed coupled model on fluvial flooding assessment is then assessed and compared with a well-recognized commercial software (HEC-RAS model) through an idealized fluvial case and an extensively studied real-scale fluvial case in the Severn River Basin. Based on the simulated results concerning the numerical accuracy, the coupled model is found to give similar results in the aspects of the river flow and overland flow modeling in both two study cases, which demonstrates the effectiveness of the linking methodology between the 1D-RFM and 2D-OFM-CA. From the viewpoint of numerical efficiency, the coupled model is 47% and 41% faster than the HEC-RAS model in the two cases, respectively. The above results indicate that the coupled model can reach almost the same accuracy as the HEC-RAS model with an obvious reduction in its computational time. Hence, it is concluded that the coupled model has considerable potential to be an effective alternative for fluvial flooding assessment in the river basin.

We develop a hierarchy of simplified ocean models for coupled ocean, atmosphere, and sea ice climate simulations using the Community Earth System Model version 1 (CESM1). The hierarchy has four members: a slab ocean model, a mixed-layer model (MLM) with entrainment and detrainment, an Ekman MLM, and an ocean general circulation model (OGCM). Flux corrections of heat and salt are applied to the simplified models ensuring that all hierarchy members have the same climatology. We diagnose the needed flux corrections from auxiliary simulations in which we restore the temperature and salinity to the daily climatology obtained from a target CESM1 simulation. The resulting three-dimensional corrections contain the interannual variability fluxes that maintain the correct vertical gradients of temperature and salinity in the tropics. We find that the inclusion of mixed-layer entrainment and Ekman flow produces sea surface temperature and surface air temperature fields whose means and variances are progressively more similar to those produced by the target CESM1 simulation. We illustrate the application of the hierarchy to the problem of understanding the response of the climate system to the loss of Arctic sea ice. We find that the shifts in the positions of the mid-latitude westerly jet and of the Inter-tropical Convergence Zone (ITCZ) in response to sea-ice loss depend critically on upper ocean processes. Specifically, heat uptake associated with the mixed-layer entrainment influences the shift in the westerly jet and ITCZ. Moreover, the shift of ITCZ is sensitive to the form of Ekman flow parameterization.

Uneven settlement caused by excessive exploitation of groundwater will seriously affect the smooth operation of high-speed railways. This study takes the Jinwei high-speed railway as an example to explore the development characteristics and distribution of groundwater and land subsidence along the railway under the influence of groundwater exploitation. Based on the comprehensive analysis of hydrogeological conditions and soil characteristics, a three-dimensional coupling model of groundwater seepage and land subsidence was established. The groundwater flow field and land subsidence along the railway under different mining schemes were quantified, and the prevention and control scheme to ensure the smooth operation of the high-speed railway was determined. The results show that the coupling model verified by groundwater and subsidence monitoring data can better simulate the development process of land subsidence. The subsidence center along the railway line is located between DK315 ∼ DK327, with a predicted maximum subsidence rate of 16.36 mm/a. The second most serious area is located between DK295 ∼ DK309, with a maximum subsidence rate of 12.21 mm/a. The maximum ban on mining along the railway is extended to 350 m at the section DK295 ∼ DK309, and to 450 m at the section DK315 ∼ DK325, which can minimize the impact of land subsidence on the high-speed railway. [ABSTRACT FROM AUTHOR]

The effect of Stokes drift production (SDP), which includes Coriolis-Stokes forcing, Langmuir circulation, and Craik-Leibovich vortexes, on the upper ocean during typhoon passage in the Bohai Sea (BS), China, is investigated by using a coupled wave-current model. The role of SDP in turbulent mixing and the further dynamics during the entire typhoon period are comprehensively studied. Experimental results show that SDP greatly increases turbulent mixing at all depths under typhoon conditions by up to seven times that under normal weather conditions. SDP generally strengthens sea surface cooling by more than 0.4°C, with the maximum reduction in sea surface temperature (SST) at the during-typhoon stage exceeding 2°C, which is approximately seven times larger than that under normal weather conditions. The SDP-induced decrease in current speed can exceed 0.2 ms−1, and the change in current direction is generally opposite the wind direction. These results suggest that Stokes drift depresses the effect of strong winds on currents by intensifying turbulent mixing. Mixed layer depth (MLD) is distinctly increased by O(1) during typhoons due to SDP and can deepen by more than 5 m. In addition, the continuous effects of SDP on SST, current, and MLD at the after-typhoon stage indicate a hysteretic response between SDP and typhoon actions. [ABSTRACT FROM AUTHOR]

This paper addresses the design and validation of High-Order Absorbing Boundary Conditions (HABC) of the Padé family on a Coupled Hydrodynamic Wave Model (CHWM) especially with surface tension effect (with small spatial scales). Inspired by the Neumann–Kelvin model, the CHWM comprises a fluid model enabling the consideration of multiple objects located immediately beneath the surface, coupled with a free surface model that incorporates a small added mass surface term. With the surface tension effect, we introduce new coefficients (similar to Higdon coefficients) on each HABC (for the surface model and the basin model) to ensure the continuity of the two HABC at the interface between the coupled models. Consequently, we propose a useful specific compatibility condition, and a significant reduction of the Padé approximation particularly in the water case. [ABSTRACT FROM AUTHOR]

Simulating river–lake systems while accounting for climate change and human activity is challenging, particularly when dealing with the complex interactions between rivers and lakes. In this study, we developed an integrated model coupling long short-term memory (LSTM), a two-dimensional hydrodynamic model (NewFlood), and the time-variant gain model (TVGM). We applied and validated this model using the Yangtze River–Poyang Lake system. The coupled model accurately and efficiently simulated the water levels, streamflow, and water exchange between the Yangtze River and Poyang Lake. The average Nash-Sutcliffe efficiency coefficient of the coupled model reached 0.92, indicating high simulation accuracy. The coupled model holistically accounts for the impacts of climate change and human activities on the spatiotemporal dynamics of river–lake systems, providing a robust scientific basis for quantifying the relative contributions of different factors influencing river–lake interactions. [ABSTRACT FROM AUTHOR]

Hydrodynamic calculation is considered to be significantly important to ensure the safe operation of boiler during the peak-shaving process. An accurate furnace heat flux distribution is the basis for the accurate hydrodynamic calculation. To investigate the hydrodynamic characteristics of a 600 MW boiler, a coupled model that consists of combustion simulation and hydrodynamic calculation is applied in this study. The numerical simulation could provide the distribution of the furnace heat flux as a preparation for the hydrodynamic calculation. Results show that the calculated value of the hydrodynamic characteristics agrees well with the measured one. The pressure drop differences of the steam system between the calculated and measured values are 0.04, 0.02, 0.13, and 0.05 MPa under 100% boiler maximum continuous rating (BMCR), 75% turbine heat acceptance (THA), 50% BMCR, and 30% BMCR loads, respectively. The relative error of the mass flux distribution increases as operating load decreases, reaching a maximum (7.63%) under 30% BMCR load. For the four loads discussed in this study, the greatest temperature of the working fluid is 681.0 K, while the fin-center temperature jumps from 708.0 to 801.7 K under 100% BMCR load. The present study is intended to improve the method of the hydrodynamic performance calculation, which would benefit the safety operation of boiler during the peak-shaving process. [ABSTRACT FROM AUTHOR]

The performance of the operational Extended-range forecast (ERF) issued by IMD for the recent two monsoon seasons (2020 and 2021) at 676 districts over India has been evaluated. The ERF prepared in real-time up to 4 weeks is evaluated at the district level in terms of predicting above-normal (AN), normal (NN) and below-normal (BN) rainfall. Statistical scores like Forecast Accuracy, Bias Score (BS), Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), Equitable Threat Score (ETS) etc. have been calculated for 'AN' 'NN' and 'BN categories separately at the district level. During the 2020 monsoon season, the forecast accuracy in terms of predicting 'above-normal' normal and below-normal categories show 65–68% for the week 1 forecast and it gradually decreases to about 52–56% in week 4 forecasts, whereas, for 2021 monsoon season it is slightly higher by 2% to 4%. The BS during both seasons tends to overpredict the above-normal categories and under-predict the below-normal category, whereas the normal category indicates much higher BS values indicating over-prediction. The POD, FAR, CSI, and ETS values also show reasonable scores up to 2 weeks for 'AN' and 'BN' forecasts with the 2021 monsoon season having slightly higher compared to 2020. The present analysis shows encouraging results for at least up to two weeks with relatively higher skill. Thus, the Extended-rage time scale at the district level results shows very encouraging results for at least up to 2 weeks for various applications, although it has the scope for further improvement. [ABSTRACT FROM AUTHOR]

Floating slab tracks (FSTs) are used to reduce the impact of vibration on precision instruments and historical relics along metro lines; however, ground vibration is universally amplified at the natural frequency of the tracks. In this study, a full-frequency control method that considers frequency matching for environmental vibrations, in combination with metro vibration sources and propagation paths, was developed based on the bandgap theory of the periodic structure. The effectiveness of this method was analysed by establishing a three-dimensional metro train–FST coupled model and a finite element analysis model of track bed–tunnel–soil–row piles. The results show that ground vibration can be reduced by approximately 3–5 dB at the natural frequency of the FST by adjusting the bandgap range of the periodic piles to 7–9 Hz, eliminating the adverse effect of vibration amplification at the natural frequency of the FSTs. The proposed control method shows good vibration control effects and can effectively minimise ground vibration in the full-frequency range. [ABSTRACT FROM AUTHOR]