High Inflow Research Articles

Mode recognition in a kerosene-fueled scramjet combustor by a Swin Transformer neural network

Recognizing the combustion mode in scramjet engines is critical for suppressing oscillations and stabilizing the combustion process in hypersonic aircrafts. Current accesses mainly depend on mechanical measurement and dominant frequencies based on image analysis methods, such as proper orthogonal decomposition and dynamic mode decomposition. However, these traditional methods either lack of precision or fall short of the need for prior knowledge, poor generalization, and low efficiency, posing challenges in practical implementations, especially when online controlling is highlighted in the scramjet combustions. Recently, machine learning (ML) has been introduced to the combustion community due to its superiority in high flexibility and efficiency in addressing complex problems. The classical convolutional neural network (CNN) architectures have been reported to achieve efficient combustion mode recognition in furnace combustion, swirling combustor, and rotating detonation engines. However, those CNN-based models are incapable of utilizing the global flame features and the coherences of local areas, resulting in insufficient accuracy and robustness in scramjet combustions with high inflow speed and distinct mode variations. To address this problem, this paper reports a Swin (shifted window) Transformer model, an advanced ML structure outstanding in capturing both global and local features by its self-attention mechanism with high computational efficiency, to identify combustion modes in scramjet engines. The Swin-T was trained and validated in a kerosene-fueled cavity-based scramjet combustor, and results show that it can achieve a considerable accuracy of 95.28%. Comparisons with CNN-based models further indicate that Swin-T outperforms in accuracy, efficiency, and robustness by around 0.7%, 80%, and 3%, respectively.

Proximal protection devices for carotid artery stenting - A benchtop assessment of flow reversal performance.

Proximal protection devices, such as TransCarotid Artery Revascularization (TCAR, SilkRoad Medical, Sunnyvale), aim to yield better outcomes in carotid artery stenting (CAS) than distal protection devices by preventing plaque embolization to the brain. However, transfemoral catheters may not fully reverse flow from the external carotid artery (ECA) to the internal carotid artery (ICA). We assess a new balloon-sheath device, Femoral Flow Reversal Access for Carotid Artery Stenting (FFRACAS), for this purpose. The FFRACAS prototype (ID = 0.117"; L=80cm) was compared to TCAR (ID=0.104", L=30cm) and MoMa (Medtronic, Minneapolis; ID=0.083", L=90cm) in a pulsatile flow model with blood simulant at 800mL/min. MoMa was used according to labeled instructions, with both CCA and ECA balloon inflation, without CCA-femoral vein shunt placement, and in an off-label fashion with single balloon occlusion in the CCA and shunt. Flow rates of the ICA, ECA, and shunt, when applicable, were monitored during CAS stages: CCA flow arrest, shunt activation, and stent delivery. Experiments were conducted under two ECA inflow conditions (-10 and -20 mL/min). Statistical comparison of ICA flow rates was conducted using ANOVA and Tukey's post-hoc tests. MoMa's on-label use maintained retrograde ICA flow (-0.3 mL/min) throughout CAS. Upon shunt activation, TCAR and FFRACAS reversed ICA flow similarly under low ECA inflow (ICA=-5.10 mL/min vs. -4.83 mL/min; p=0.349), but neither achieved ICA flow reversal under high ECA inflow or during stent delivery. MoMa off-label use failed to reverse ICA flow. FFRACAS presents a potential alternative to TCAR, achieving similar degrees of flow reversal from a transfemoral approach to that achieved with the transcarotid approach. The MoMa system reliably prevents anterograde flow in ICA during CAS. CAS = Carotid Artery Stenting; TCAR = Transcarotid Arterial Revascularization; CCA = Common Carotid Artery; ICA = Internal Carotid Artery; ECA = External Carotid Artery; VA = Vertebral Artery; FFRACAS = Femoral Flow Reversal Access for Carotid Artery Stenting; ID = Inner Diameter; OD = Outer Diameter.

Unraveling the Relationships between Trend of Dam Inflows, Hydrometeorological Variables, and Vegetation in Western and Southwestern United States

Abstract This paper explored temporal changes in magnitude and seasonality of low, median, and high inflows of 51 dams across the western and southwestern United States over the 1993–2022 period. Changes in precipitation, air temperature (an indicator of snowpack and evaporation), soil moisture, and vegetation were also examined to identify potential reasons for the temporal trends in dam inflows. Using monotonic and nonmonotonic tests, we found a general downward trend in dam inflows, particularly across the Upper Colorado and California regions. More than 30% of the dams showed a downward trend in their annual median inflows, high inflows during spring, and median inflows during fall. The downward trend of dam inflows was associated with decreasing precipitation and soil moisture and increasing temperatures. While vegetation exhibited positive associations with inflows, it did not seem to be a primary factor for explaining the inflow trends. We also observed shifts in the seasonality of low and high inflows; there was an increase in the proportion of inflows occurring during summer and fall and a decrease in winter proportions for low inflows. Similarly, high inflows exhibited an increase in spring proportions and a decrease in fall proportions. Our changepoint analyses detected nonmonotonic trends between 2002 and 2012 in ∼13% of the dams; the majority were located in the Upper Colorado and California regions. More than half of these changepoints were in 2011, likely due to widespread droughts then. Our study has implications for reservoir managers to identify changes that dams experience over time and assist them in proposing actions that maintain the dams’ functionality.

Influence of sweep angle on leading edge vortex dynamics of a fully passive oscillating-plate hydrokinetic turbine prototype

The present work assesses the use of spanwise flow in enhancing the performance of the fully passive oscillating-plate hydrokinetic turbine prototype by relating the dynamics of the leading edge vortex (LEV) to the power extraction performance. Two-dimensional (2D) planar and three-dimensional (3D) tomographic particle image velocimetry were employed to obtain quantitative flow structure of oscillating-plates undergoing heave and pitch motion in uniform inflow at Reynolds number of 21 000. A plate with a 6° sweep angle and an unswept plate (control case) were considered in the present study. Dynamics of the LEV were investigated using the patterns of the phase-averaged vorticity during the oscillation cycle. The 3D vector fields provided insights into the spanwise variation of the vortical structure and the rate of deformation of the vortex, which was determined by calculating the deformation terms in the vorticity transport equations which are related to the stability of the vortex. The results show evidence of a delay in the shedding of the LEV and an increase in its stability in the case of the swept plate, compared to the control case, which in turn benefit the power extraction performance at high inflow velocities.

THE IMPACT OF INFLOW UNSTEADINESS ON LOSS PREDICTION

Abstract Stagnation pressure loss coefficient is still the most commonly used loss metric for performance evaluation and is routinely used to validate simulations. This is because it is easy to measure and readily available from the experiments. However, it was previously shown (TURBO-24-1006) that the stagnation pressure loss coefficient can become unreliable when high levels of inflow unsteadiness are present. As the current design trends are moving towards more compact machines and higher work coefficients, the levels of unsteadiness are likely to increase. It is therefore desirable to assess how higher inflow unsteadiness levels affect the performance of new blade designs and what loss metrics should be used to reliably estimate it. Motivated by the need to understand how performance prediction changes under highly unsteady inflow conditions, we perform a series of high fidelity scale resolving simulations. We use this data to construct energy budgets for a variety of mid-span compressor cases with varying Reynolds numbers and inflow turbulence intensities. This allows us to systematically assess the impact of inflow conditions on loss prediction when using stagnation pressure based loss metrics. Stagnation pressure loss coefficient was found to be least reliable for the high inflow turbulence intensities and at high Reynolds numbers.

A comparative analysis of deep-learning models for dam discharge forecasting for disaster management

ABSTRACT This paper represents a comprehensive study of dam water discharge prediction using various deep-learning models. The main aim of this paper is to provide a data-driven solution for effective water resource management and thereby controlling the effects of floods and droughts. The Malampuzha dam, which has a spillway, a right bank canal (RBC), and a left bank canal (LBC), is considered for the study. While the spillway helps to control the water level in the reservoir by allowing extra water to flow downstream during times of severe rainfall or high inflow, hence reducing the risk of floods, the LBC and RBC are intended to divert water for agriculture. Altogether, 10 years of consecutive meteorological and dam-related data are utilized for training and testing the models in forecasting water discharge through LBC, RBC, and the spillway. Different deep-learning models, namely, long short-term memory, Bi-directional long-short term memory, recurrent neural network, gated recurrent unit, one-dimensional convolutional neural network (1D-CNN), deep neural network, autoencoder, and residual networks are explored in predicting the accuracy of dam water discharge. After testing eight deep-learning models, it was discovered that 1D-CNN performed well in predicting the discharge of water.

Urban transformation of lakes and its impacts on a lake series: A case study of the yele mallappa shetty lake series Bengaluru, India.

The interconnected systems of lakes of Bengaluru, India, experience tremendous stress due to unsustainable urbanisation. Traditional lake-centric research approach struggles to capture and address this issue due to the cascaded nature of impacts in interconnected lake systems. Hence, this study assesses the impact of urbanisation on a lake series scale, focusing on the Yele Mallappa Shetty Lake series (YMSLS). Land use land cover change analysis (1993-2023) showed that in 1993, the YMSLS catchment area was dominated by open spaces (53.4%) and agriculture land and vegetation (35%), with built-up areas covering only 7.2%. By 2023, the built-up area has expanded to 34.6% and became the dominant land use. This rapid urbanisation has led to increased water surface area from wastewater influx, causing significant weed growth and water pollution in the lakes. Lake water quality assessment showed that faecal coliform, total coliform, dissolved oxygen, and biochemical oxygen demand levels exceeded standard limits with spatio-temporal variations driven by interconnectivity. Pollutant flushing during monsoon reduced pollution load in upstream lakes, but high wastewater inflow made downstream lakes, particularly the end lake, highly polluted but perennial. Increased water availability expanded the user base of the end lake, but traditional uses have declined and coping strategies of users, such as wastewater lift irrigation from the lake, became unsustainable. The study indicates that spatial interdependence and cascading effects necessitate a lake series approach for assessing the impacts of urbanisation on interconnected lake system, which is crucial for enhancing water security and preparedness for future extreme events.

Effects of the inflow total temperature on the non-premixed rotating detonation engine performances

As a promising propulsion system, air-breathing rotating detonation engines (RDEs) are investigated with significant interest recently. However, simulations of air-breathing RDE with real flight condition are limited, and performance of RDEs with high inflow total temperature, as well as the influence of inflow total temperature on RDEs, needs further exploration. In this paper, simulations with four inflow total temperatures (300 K, 500 K, 700 K and 900 K) were conducted to analyze the propagation features of rotating detonation waves (RDWs) and operation modes in the RDE at low and high inflow total temperatures. Additionally, injection and mixing, as well as combustion characteristics and propulsion performance of the RDE were researched. It is found that with low inflow total temperature, single wave propagates in the combustor, which degenerates into shock wave at the outer wall due to insufficient mixing. When inflow total temperature is high, the RDE is in multi-wave operation mode and detonative combustion only occurs around the outer wall. With increase of inflow total temperature, mixability of reactants initially improves but then deteriorates slightly. Moreover, RDW propagation velocity and specific impulse of the RDE decrease. Though fuel utilization rate improves, detonation fraction drops dramatically and parasitic combustion fraction rises significantly, resulting from intensification of pre-combustion. Particularly, the detonation fraction is only 16.7 % and parasitic combustion fraction reaches up to 56.35 % at inflow total temperature of 900 K. Furthermore, regardless of the variation of inflow total temperature, detonative combustion is prominent in the premixed combustion mode, and the peak fraction of detonation appears at the off-stoichiometric ratio.

Magnetising galaxies with cold inflows

Context. High-redshift (z ∼ 2 − 3) galaxies accrete circumgalactic gas through cold streams. Recent high-resolution magnetohydrodynamic (MHD) simulations of these streams show a significant amplification of the intergalactic magnetic field in the shear layer around them. Aims. For this work we estimated the magnetisation of high-redshift galaxies that would result purely due to the accretion of already magnetised gas from cold streams. Methods. We used the mass inflow rates and saturated magnetic field values from cold stream simulations as input to a simple analytic model that calculates the galactic magnetic field purely from mass accretion. Results. Our model predicts average magnetic field strengths that exceed μG values at z ∼ 2 − 3 for inflow rates above 0.1 M⊙ yr−1. For high inflow rates, our model results are consistent with the recent detection of a strong magnetic field in z ≳ 2.6 galaxies. Conclusions. Within the assumptions of our simple model, magnetised cold streams emerge as a viable mechanism for seeding a dynamically important galactic magnetic field.

Three-Dimensional (3D) Flood Simulation Aids Informed Decision Making: A Case of a Two-Story Underground Parking Lot in Beijing

Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment.

The Impact of Digital Talent Inflow on the Co-Agglomeration of the Digital Economy Industry and Manufacturing

The co-agglomeration of the digital economy industry and manufacturing is significant for addressing issues such as being “large but not strong” and “comprehensive but not refined” in China’s manufacturing sector. This study uses 269 cities in China from 2006 to 2022 as the research sample, innovatively employing data from digital economy enterprises and manufacturing enterprises to measure industrial co-agglomeration, and comprehensively analyzes the mechanism of how the inflow of digital talents influences the co-agglomeration of the digital economy industry and manufacturing. The findings are as follows: (1) From 2006 to 2022, the inflow of digital talents and the level of co-agglomeration between the digital economy industry and manufacturing in Chinese cities have consistently risen, generally moving towards higher inflow and higher levels of co-agglomeration. However, the inflow of digital talent in the central and western regions is relatively low, with most cities still facing difficulties due to inadequate policy support and resource investment. Industrial co-agglomeration exhibits characteristics of “core–periphery”, “multi-core agglomeration”, and “gradient diffusion” coexisting. (2) The flow of digital talents can significantly promote the co-agglomeration of the digital economy industry and manufacturing, and this conclusion remains valid after robustness testing. The flow of digital talents drives the co-agglomeration of the digital economy industry and manufacturing by enhancing the level of digital technology innovation, promoting the spillover and flow of digital knowledge, increasing the entrepreneurial activity of urban digital economy enterprises, and upgrading industrial structures. Furthermore, digital economy policies play a regulatory role in this process. (3) The promotion effect of digital talent inflow is more pronounced in low- and mid-end manufacturing, high-grade cities, well-developed digital infrastructure, and non-resource-based cities. By contrast, this effect is relatively weaker in high-end manufacturing and low-grade cities. In cities with weak digital infrastructure and resource-based cities, this effect is not significant. (4) The inflow of digital talents and the co-agglomeration of digital economy industry and manufacturing have a significant promotion effect on cities with similar economic development levels and adjacent geographical locations, demonstrating a positive diffusion effect.

Contribution of groundwater-borne nutrients to eutrophication potential and the share of benthic algae in a large lowland river

Groundwater inflow can be a significant source of nutrients for riverine ecosystems, which can affect eutrophication i.e., the elevated primary production and the corresponding accumulation of algal biomass. Experimental and modelling work has shown that benthic algae (autotrophic biofilms) in particular benefit, as they have direct access to the inflowing groundwater-borne nutrients. Primarily the supply of phosphorus (P) enhances pelagic algal biomass, as it is the limiting nutrient for primary production in most freshwater systems. In this study, we estimate the effect of groundwater inflow on overall eutrophication of a large, European lowland river and tested its seasonal effect on biofilms in particular. We calculated the effects on overall eutrophication during summer according to the estimated input of groundwater-borne P and the C:P stoichiometry of planktonic algae in the Elbe River. Our model indicated that these diffuse P inputs have the potential to significantly increase eutrophication. Groundwater-P can contribute up to 1.5 t/d PO4 over the investigated 450 km stretch of the Elbe River under low flow conditions. This would result in an additional planktonic load of about 46 t/d of particulate organic carbon, thereby contributing to eutrophication at the regional scale in this river. In contrast, at the local scale, biofilms were collected seasonally from artificial substrata exposed in the river either in hydrogeologically active areas with groundwater inflow, or in areas of varying hydraulic connectivity. Analyses of biofilm macronutrients, structural components and biofilm community composition show distinct effects of season, hydrogeology and groundwater inflow. The dominant predictors were season and the interaction between hydrogeology and groundwater. Benthic eutrophication is most likely to occur in autumn in areas of loose rock with high groundwater inflow. The strong interaction of environmental factors in determining benthic eutrophication highlights the need to assess these factors in combination rather than in isolation.

Modeling cardiac microcirculation for the simulation of coronary flow and 3D myocardial perfusion

Accurate modeling of blood dynamics in the coronary microcirculation is a crucial step toward the clinical application of in silico methods for the diagnosis of coronary artery disease. In this work, we present a new mathematical model of microcirculatory hemodynamics accounting for microvasculature compliance and cardiac contraction; we also present its application to a full simulation of hyperemic coronary blood flow and 3D myocardial perfusion in real clinical cases. Microvasculature hemodynamics is modeled with a compliant multi-compartment Darcy formulation, with the new compliance terms depending on the local intramyocardial pressure generated by cardiac contraction. Nonlinear analytical relationships for vessels distensibility are included based on experimental data, and all the parameters of the model are reformulated based on histologically relevant quantities, allowing a deeper model personalization. Phasic flow patterns of high arterial inflow in diastole and venous outflow in systole are obtained, with flow waveforms morphology and pressure distribution along the microcirculation reproduced in accordance with experimental and in vivo measures. Phasic diameter change for arterioles and capillaries is also obtained with relevant differences depending on the depth location. Coronary blood dynamics exhibits a disturbed flow at the systolic onset, while the obtained 3D perfusion maps reproduce the systolic impediment effect and show relevant regional and transmural heterogeneities in myocardial blood flow (MBF). The proposed model successfully reproduces microvasculature hemodynamics over the whole heartbeat and along the entire intramural vessels. Quantification of phasic flow patterns, diameter changes, regional and transmural heterogeneities in MBF represent key steps ahead in the direction of the predictive simulation of cardiac perfusion.

Middle Eastern carbonate reservoirs – the critical impact of discrete zones of elevated permeability on reservoir performance

Abstract Middle Eastern carbonate petroleum reservoirs exhibit a range of heterogeneities which consist of variable combinations of primary stratigraphic and secondary diagenetic and structural characteristics. These produce diverse permeability architectures which can exert a profound influence on reservoir performance during secondary recovery. Of particular importance are laterally persistent discrete zones of elevated permeability (DZEP) that typically make up a volumetrically minor proportion of the reservoir yet show disproportionately high fluid inflow or outflow. The stratigraphic, diagenetic and structural origins of elevated permeability in Middle Eastern carbonate reservoirs are considered here and the consequences of such features for reservoir performance are discussed. The term DZEP denotes geological sources of elevated permeability at least an order of magnitude greater than background reservoir properties. Stratigraphically organized DZEP comprise coarse-grained layers, event beds or parasequence tops or bases in neritic or platform interior settings. Other origins include bioturbated layers, grainy clinothems and bed-scale, grain-size variations in shoal deposits. Diagenetic DZEP are typically dissolution horizons with mouldic and touching-vug pore networks or dolomitized intervals which often overprint stratigraphic DZEP. Structural DZEP include individual faults, fracture corridors and fracture concentrations related to mechanical stratigraphy. During production through natural pressure depletion, DZEP may dominate well productivity. Under secondary recovery, the same intervals may dominate inter-well fluid flow, causing flood conformance issues, cross-zone fluid movement, bypassed pay and earlier-than-expected water or gas breakthrough to production wells. Optimization of production and ultimate recovery rely on collecting the correct kinds of data at a sufficiently early stage in the reservoir characterization process to permit their inclusion in static and dynamic reservoir models.

Effects of calcium carbide slag on properties and carbon sequestration efficiency of cement pastes mixed under direct CO2 injection conditions

CO2-mixing by directly injecting CO2 into fresh cement-based materials is a burgeoning technology to produce low-carbon cement products. The objective of this study is to investigate the influence of the calcium carbide slag (CCS) content on the properties and carbon sequestration efficiency of cement pastes mixed under direct CO2 injection conditions. The results indicate that the addition of CCS reduced the fluidity of the cement pastes, accelerated the setting process, increased volume shrinkage, and reduced compressive strength. Following the injection of CO2 into the cement pastes, calcium hydroxide (CH) was carbonated to form calcium carbonate (CC) particles which fill the voids in the cement pastes, thereby reducing volume shrinkage and increasing compressive strength. A lower CO2 inflow rate (2 L/min) was more beneficial to the workability of the cement pastes, while a high inflow rate (6 L/min) can lead to insufficient hydration and affect the development of strength. However, a higher CO2 inflow rate was favorable for improving carbon sequestration efficiency. The highest amountof carbon sequestration can be reached at 6.93 %, when the CCS content is 10 % and the CO2 inflow rate is 6 L/min.

Experimental and numerical investigation on the potential of wake mixing by dynamic yaw for wind farm power optimization

This study investigates open-loop dynamic yaw control as a strategy for enhancing wind farm performance through wake mixing. The focus is on understanding the potential for enhanced wake mixing under different turbulence intensities, and the mechanisms triggering mixing. Experimental tests are conducted using scaled wind tunnel experiments with two model wind turbines. The wake flow is analysed by large eddy simulations (LES). Dynamic yawing is prescribed by sinusoidally varying the yaw angle at different excitation frequencies. The study reveals that dynamic yaw control, particularly at low inflow turbulence, leads to increased wake mixing. The resulting enhanced wind farm power capture has a rather flat maximum around an optimal Strouhal number. This is in contrast to high inflow turbulence, where the effectiveness of the control strategy is significantly reduced. The meandering motion of the wake induced by dynamic yaw excitation is identified as the key mechanism for improved wake recovery.

Denitrifying bioreactors and dissolved phosphorus: Net source or sink?

Understanding the world through a lens of phosphorus (P), as Dr. Andrew Sharpley aimed to do, adds a deeper dimension for water quality work in the heavily tile-drained US Midwest where nitrate is often the nutrient of biggest concern. Denitrifying woodchip bioreactors reduce nitrate pollution in drainage water, but dissolved phosphorus leached from the organic fill is a possible pollution tradeoff. Recent work by Dr. Sharpley and others defined such tradeoffs as strategic decisions in which a negative outcome is accepted with prior knowledge of the risk. In this vein, we assessed 23 site-years from full-size bioreactors in Illinois to determine if bioreactors were a net dissolved reactive phosphorus (DRP) source and, if so, to determine flow-related correlation agents (1904 sample events; 10 bioreactors). DRP was removed across the bioreactors in 15 of 23 site-years. The 23 site-years provided a median annual DRP removal efficiency of 12% and a median annual DRP removal rate of 7.1mg DRP/m3 bioreactor per day, but the ranges of all removal metrics overlapped zero. The highest daily bioreactor DRP removal rates occurred with high inflow concentrations and under low hydraulic retention times (i.e., under higher loading). Dr. Sharpley was one of the first to explore losses of DRP in subsurface drainage and performed decades of useful applied studies that inspired approaches to management of P loss on both drained and undrained land. We seek to honor this legacy with this practical study of the DRP benefits and tradeoffs of denitrifying bioreactors.

Adapting reservoir operations for optimal water management under varying climate and demand scenarios using metaheuristic algorithms

The operational rule curve is significant for proper reservoir operations and water resources management of the dam. The optimisation of the release policy is rather a complicated and stochastic problem. Various types of algorithms have been used to develop the release policy for the Klang Gate Dam (KGD), but alas, climate parameters associated with climate change, be it regional or globally, e.g., temperature factors, had not been considered then. In this study, the consideration of maximum and minimum temperature factors is given emphasis, while water demand is evaluated in the optimisation problem using simulation-optimisation approaches. The support vector regression simulation model (SVRS), and the multilayer perceptron simulation model (MLPS) were used to simulate the demand for the scenario cases. SVRS utilises the hyperplane theory to study the relationship between the input and output data, whereas MLPS employs the human neural system to weight and process the inputs via multiple layers of neurons into a targeted output. Four distinct types of simulation-optimisation combination model, including the SVRS-firefly algorithm (SVRS-FA), the SVRS-particle swarm optimisation (SVRS-PSO), the MLPS-firefly algorithm (MLPS-FA), and the MLPS-particle swarm optimisation (MLPS-PSO), were applied and investigated. The ultimate goal of this study was to minimise the water deficit. The PSO optimisation models overall have outperformed the FA optimisation models in all aspects. The periodic reliability of the MLPS-PSO was found to be the highest when the minimum temperature scenario was considered, and is 0.6491, with the least shortage period of 80 months. The MLPS-PSO is also the most resilient model in the same scenario, with a resilience value of 0.6750. Whereas the SVRS-PSO was the least vulnerable model in the minimum temperature scenario with the lowest shortage index of 0.0047 and a volumetric deficiency of about 2.44 MCM in total. The SVRS-PSO model showed excellent performance for high and low inflow conditions, while the MLPS-PSO model was better during medium inflows. In short, each of the models investigated has its particular field of advancement, but since the maximum temperatures sounded critical, additional research for the maximum temperature case could be pursued further in depth.

Burial of Organic Carbon in Swedish Fjord Sediments: Highlighting the Importance of Sediment Accumulation Rate in Relation to Fjord Redox Conditions

AbstractFjords are net carbon sinks with high organic carbon (OC) burial rates; however, the key drivers of OC burial in these systems are not well constrained. To study the role of water column redox condition and OC composition on OC preservation in fjord sediments, we determined OC accumulation rates (OCAR), OC source, and OC degradation in three Swedish fjords with variable redox conditions (long‐term oxic, seasonally hypoxic, and long‐term anoxic). Average OCARs were variable between and within the fjords studied (2–122 g OC m−2 yr−1), but highest rates were at the mouth for each fjord. Based on a δ13C mixing model, Swedish fjords bury predominantly marine‐derived OC (∼83% of the total OC burial) likely because of relatively gentle slopes, low riverine discharge, and high marine inflow. Using a multi‐biomarker approach (lignin, photosynthetic pigments, and total hydrolyzable amino acids) we found, terrestrially‐ and marine‐derived OC were moderately degraded under the various redox conditions sampled, suggesting water column redox and OC source are not primary drivers of OC burial in these fjords. Rather, high sediment accumulation rates, common to fjords globally, lead to low oxygen exposure times, thus promoting efficient burial of OC regardless of its chemical composition.

Examining the Coopetition Relationships in Renewable Energy Trade among BRI Countries: Complexity, Stability, and Evolution

The Belt and Road Initiative (BRI) has significantly transformed the traditional energy market and reshaped international cooperation and conflict dynamics through its expanding trade in renewable energy resources. This study focuses on examining the complex and evolving nature of coopetition relationships in the renewable energy trade among BRI countries from 2013 to 2020. Understanding the interplay between cooperation and competition in this sector is crucial for comprehending the dynamics and stability of these trade relationships. Using a signed network approach, the findings of this study reveal that the countries predominantly exhibit a cooperative relationship. However, as time progresses, a notable pattern emerges, characterized by the coexistence of “competitive cooperation” and “cooperative competition”. In addition, coopetition group clustering is strongly influenced by geographical location. China, as a key player in the BRI, demonstrates a coopetition group characterized by a high inflow and low outflow pattern. Furthermore, the implementation of the BRI has greatly improved the overall stability of trade along the route. However, the coexistence of competition and cooperation among nations has increased the uncertainty of trade relations, thereby exerting a certain level of influence on their stability. Based on these findings, this study proposes policy recommendations to strength renewable energy trade relationships along the BRI route.